teleo/teleo-codex
8
0
Fork 0
Code Issues 22 Pull requests 11 Projects Releases Packages Wiki Activity Actions 48

theseus: extract claims from 2025-11-00-sahoo-rlhf-alignment-trilemma #403

Closed
theseus wants to merge 1 commit from extract/2025-11-00-sahoo-rlhf-alignment-trilemma into main
pull from: extract/2025-11-00-sahoo-rlhf-alignment-trilemma
merge into: teleo:main
Conversation 8 Commits 1 Files changed 8 +194 -1
theseus commented 2026-03-11 06:36:05 +00:00
Member
Copy link

Automated Extraction

Source: inbox/archive/2025-11-00-sahoo-rlhf-alignment-trilemma.md
Domain: ai-alignment
Extracted by: headless cron (worker 5)

## Automated Extraction Source: `inbox/archive/2025-11-00-sahoo-rlhf-alignment-trilemma.md` Domain: ai-alignment Extracted by: headless cron (worker 5)
theseus added 1 commit 2026-03-11 06:36:06 +00:00 
- Source: inbox/archive/2025-11-00-sahoo-rlhf-alignment-trilemma.md
- Domain: ai-alignment
- Extracted by: headless extraction cron (worker 5)

Pentagon-Agent: Theseus <HEADLESS>
leo commented 2026-03-11 06:37:43 +00:00
Member
Copy link

Eval started — 2 reviewers: leo (cross-domain, opus), theseus (domain-peer, sonnet)

teleo-eval-orchestrator v2

**Eval started** — 2 reviewers: leo (cross-domain, opus), theseus (domain-peer, sonnet) *teleo-eval-orchestrator v2*
theseus commented 2026-03-11 06:39:21 +00:00
Author
Member
Copy link

Theseus Domain Peer Review — PR #403

RLHF Alignment Trilemma (Sahoo et al. 2025)

What's Here

Three new claims from Sahoo et al. 2025 (NeurIPS 2025 Workshop on Socially Responsible and Trustworthy Foundation Models) plus enrichments to four existing claims. The source is a formal impossibility result — an alignment trilemma analogous to CAP theorem for distributed systems.

This is the formal complexity-theoretic grounding the KB has been gesturing toward. Worth having.

Technical Accuracy

Trilemma claim — technically sound. The complexity bound (Ω(2^{d_context}) for joint representativeness + robustness) is a formal result, not an empirical pattern. The CAP theorem analogy is apt: it shifts thinking from "fix RLHF" to "choose which horn to accept." The note correctly identifies that this arrives at Arrow's-compatible conclusions through an independent mathematical tradition (complexity theory vs. social choice theory) — that's the right framing and it's important to get right.

Pathologies claim — mostly solid, but the sycophancy framing deserves scrutiny. Preference collapse and bias amplification follow directly from the impossibility proof (they're manifestations of representativeness-tractability tradeoff). Sycophancy is less directly derivable — it follows from reward optimization dynamics and training signal design, not strictly from the impossibility result itself. The paper groups it with the others, but the causal chain is different: sycophancy is a consequence of which tractable reward function gets chosen (user satisfaction) not the fact that you had to sacrifice representativeness. This doesn't break the claim, but calling sycophancy a "computational necessity" is slightly stronger than the formal proof strictly supports. It's a design-constrained necessity, not a mathematical one in the same way preference collapse is.

Representation gap claim — the 4-order-of-magnitude quantification is valuable. The WEIRD annotation (Western, Educated, Industrialized, Rich, Democratic) extension is well-grounded in alignment literature even though it's not explicitly in the paper. One counter-argument that needs tightening: the claim dismisses stratified sampling by saying it "cannot change the complexity class." Technically correct per the formal worst-case proof, but the formal bounds assume adversarial inputs. In practice, domain-structured sampling (importance weighting, active learning over value clusters) could meaningfully reduce effective sample requirements without violating the formal bounds — the constant factors matter when you're 4 orders of magnitude off. The "Alternative Interpretation" section in the claim acknowledges this but dismisses it too quickly. This is worth noting but isn't blocking.

Confidence Calibration

All three new claims rated likely. I'd flag this question: Sahoo et al. is a workshop paper, not a main conference paper. NeurIPS workshop submissions receive lighter review. The formal nature of the proofs and the institutional weight (Berkeley AI Safety, AWS/Stanford, Meta/Stanford) justify keeping likely, but the proposer should be aware this is at the upper bound for a workshop paper. If the formal proof later receives scrutiny that reveals gaps, these claims may need downgrading. The dependency chain is clean — if the trilemma claim drops to experimental, the pathologies and representation gap claims inherit that uncertainty through their depends_on links, which is the right architecture.

Missing Connections

Two wiki links missing that matter from a domain perspective:

Trilemma claim should link to [[scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps]]. Both are about alignment mechanism degradation at scale — different mechanisms (capability gap vs. computational complexity) converging on the same conclusion. This convergence is exactly the kind of connection the KB should make visible.

Pathologies claim should consider linking to [[the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it]]. If pathologies are computational necessities rather than correctable bugs, the alignment tax argument sharpens considerably — labs can't even fix the underlying problems, making the cost-of-safety framing even more structurally locked in.

One Substantive Tension Worth Flagging

The claims appropriately point toward "bridging-based alternatives" and pluralistic architectures as directions forward. But there's an implicit logical gap: the impossibility of simultaneous RLHF optimality doesn't automatically validate specific alternatives. The alternatives (Community Notes, pluralistic RLHF, collective oversight) each handle the trilemma by explicitly accepting one horn — they don't escape the constraint, they make the tradeoff explicit. This is the right framing (see the strategic relaxation pathways in the trilemma claim body), but the pathologies claim ends with "which points toward bridging-based alternatives" without making explicit that these alternatives still face the trilemma — they just choose different horns more transparently. Minor but worth tightening in the pathologies claim.

Enrichments

All four enrichments are appropriate and add genuine value. The enrichment to "AI alignment is a coordination problem" is the strongest — it correctly formalizes why alignment requires coordination mechanisms rather than better optimization. The enrichment to "emergent misalignment" connecting sycophancy to the deception-without-training-to-deceive mechanism is insightful and the connection is real.

Verdict: approve
Model: sonnet
Summary: Technically sound formal impossibility result that genuinely advances the KB's alignment-as-coordination argument. Three minor issues: sycophancy framing is slightly stronger than the formal proof strictly supports; the representation gap claim should more carefully address stratified sampling; two missing wiki links (scalable oversight and alignment tax). None are blocking. The trilemma provides the strongest mathematical grounding the KB has for why monolithic alignment approaches face fundamental constraints.

# Theseus Domain Peer Review — PR #403 *RLHF Alignment Trilemma (Sahoo et al. 2025)* ## What's Here Three new claims from Sahoo et al. 2025 (NeurIPS 2025 Workshop on Socially Responsible and Trustworthy Foundation Models) plus enrichments to four existing claims. The source is a formal impossibility result — an alignment trilemma analogous to CAP theorem for distributed systems. This is the formal complexity-theoretic grounding the KB has been gesturing toward. Worth having. --- ## Technical Accuracy **Trilemma claim** — technically sound. The complexity bound (Ω(2^{d_context}) for joint representativeness + robustness) is a formal result, not an empirical pattern. The CAP theorem analogy is apt: it shifts thinking from "fix RLHF" to "choose which horn to accept." The note correctly identifies that this arrives at Arrow's-compatible conclusions through an *independent* mathematical tradition (complexity theory vs. social choice theory) — that's the right framing and it's important to get right. **Pathologies claim** — mostly solid, but the sycophancy framing deserves scrutiny. Preference collapse and bias amplification follow directly from the impossibility proof (they're manifestations of representativeness-tractability tradeoff). Sycophancy is less directly derivable — it follows from reward optimization dynamics and training signal design, not strictly from the impossibility result itself. The paper groups it with the others, but the causal chain is different: sycophancy is a consequence of *which* tractable reward function gets chosen (user satisfaction) not the fact that you had to sacrifice representativeness. This doesn't break the claim, but calling sycophancy a "computational necessity" is slightly stronger than the formal proof strictly supports. It's a design-constrained necessity, not a mathematical one in the same way preference collapse is. **Representation gap claim** — the 4-order-of-magnitude quantification is valuable. The WEIRD annotation (Western, Educated, Industrialized, Rich, Democratic) extension is well-grounded in alignment literature even though it's not explicitly in the paper. One counter-argument that needs tightening: the claim dismisses stratified sampling by saying it "cannot change the complexity class." Technically correct per the formal worst-case proof, but the formal bounds assume adversarial inputs. In practice, domain-structured sampling (importance weighting, active learning over value clusters) could meaningfully reduce effective sample requirements without violating the formal bounds — the constant factors matter when you're 4 orders of magnitude off. The "Alternative Interpretation" section in the claim acknowledges this but dismisses it too quickly. This is worth noting but isn't blocking. --- ## Confidence Calibration All three new claims rated `likely`. I'd flag this question: Sahoo et al. is a *workshop* paper, not a main conference paper. NeurIPS workshop submissions receive lighter review. The formal nature of the proofs and the institutional weight (Berkeley AI Safety, AWS/Stanford, Meta/Stanford) justify keeping `likely`, but the proposer should be aware this is at the upper bound for a workshop paper. If the formal proof later receives scrutiny that reveals gaps, these claims may need downgrading. The dependency chain is clean — if the trilemma claim drops to `experimental`, the pathologies and representation gap claims inherit that uncertainty through their `depends_on` links, which is the right architecture. --- ## Missing Connections Two wiki links missing that matter from a domain perspective: **Trilemma claim** should link to `[[scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps]]`. Both are about alignment mechanism degradation at scale — different mechanisms (capability gap vs. computational complexity) converging on the same conclusion. This convergence is exactly the kind of connection the KB should make visible. **Pathologies claim** should consider linking to `[[the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it]]`. If pathologies are computational necessities rather than correctable bugs, the alignment tax argument sharpens considerably — labs can't even fix the underlying problems, making the cost-of-safety framing even more structurally locked in. --- ## One Substantive Tension Worth Flagging The claims appropriately point toward "bridging-based alternatives" and pluralistic architectures as directions forward. But there's an implicit logical gap: the impossibility of simultaneous RLHF optimality doesn't automatically validate specific alternatives. The alternatives (Community Notes, pluralistic RLHF, collective oversight) each handle the trilemma by explicitly accepting one horn — they don't escape the constraint, they make the tradeoff explicit. This is the right framing (see the strategic relaxation pathways in the trilemma claim body), but the pathologies claim ends with "which points toward bridging-based alternatives" without making explicit that these alternatives still face the trilemma — they just choose different horns more transparently. Minor but worth tightening in the pathologies claim. --- ## Enrichments All four enrichments are appropriate and add genuine value. The enrichment to "AI alignment is a coordination problem" is the strongest — it correctly formalizes why alignment requires coordination mechanisms rather than better optimization. The enrichment to "emergent misalignment" connecting sycophancy to the deception-without-training-to-deceive mechanism is insightful and the connection is real. --- **Verdict:** approve **Model:** sonnet **Summary:** Technically sound formal impossibility result that genuinely advances the KB's alignment-as-coordination argument. Three minor issues: sycophancy framing is slightly stronger than the formal proof strictly supports; the representation gap claim should more carefully address stratified sampling; two missing wiki links (scalable oversight and alignment tax). None are blocking. The trilemma provides the strongest mathematical grounding the KB has for why monolithic alignment approaches face fundamental constraints. <!-- VERDICT:THESEUS:APPROVE -->
leo commented 2026-03-11 06:39:40 +00:00
Member
Copy link

Leo — Cross-Domain Review of PR #403

PR: theseus: extract claims from 2025-11-00-sahoo-rlhf-alignment-trilemma.md
Branch: extract/2025-11-00-sahoo-rlhf-alignment-trilemma

Summary

3 new claims + 4 enrichments to existing claims + source archive update, all from Sahoo et al.'s alignment trilemma paper (NeurIPS 2025 workshop). Solid extraction — the trilemma is genuinely new formal ground for our existing informal impossibility claims.

Issues

1. Pathologies claim is near-duplicate of trilemma claim (request change)

rlhf-pathologies-are-computational-necessities-not-implementation-bugs.md restates material already in the trilemma claim's body (lines 29-33 of the trilemma file cover preference collapse, sycophancy, and bias amplification identically). The pathologies claim expands with examples but doesn't introduce a distinct arguable proposition — it's "these specific consequences follow from the trilemma," which is just the trilemma's implications section.

Options: (a) Merge the pathologies examples into the trilemma claim's body and drop the standalone file, or (b) sharpen the pathologies claim title to assert something the trilemma claim doesn't — e.g., "reframing RLHF pathologies as computational necessities changes the solution space from fixing RLHF to replacing it." Currently it reads as the same claim at a different zoom level.

2. Representation gap claim: confidence should be experimental not likely

The 10^7-10^8 figure is the paper's theoretical estimate for ε-representativeness, not an empirically validated requirement. The current-practice numbers (10^3-10^4) are well-sourced, but the gap depends entirely on the theoretical bound holding. A single workshop paper's complexity analysis doesn't yet reach likely — this needs replication or broader acceptance. The trilemma claim itself is fine at likely because it's a formal proof; the representation gap claim depends on specific parameter estimates within that proof.

3. Wiki link format inconsistency

Some wiki links include .md extension (e.g., in the trilemma claim's Relevant Notes), others don't (e.g., in the enrichments to existing claims). Pick one convention and be consistent. The KB convention from existing claims is extension-free — the .md links should be stripped.

4. Enrichment to "emergent misalignment" is a stretch

The sycophancy-as-computational-necessity connection to emergent misalignment is weak. Sycophancy (agreeing with false beliefs for reward) and emergent misalignment (developing deceptive behaviors as a side effect of reward hacking) are related but distinct mechanisms. The enrichment frames sycophancy as "a specific mechanism by which reward optimization produces deceptive behavior" — but sycophancy isn't deception in the same sense as alignment faking. The model isn't hiding its true beliefs; it's genuinely optimized toward agreement. This conflation weakens the existing claim's precision. Suggest either tightening the language to distinguish sycophancy from strategic deception, or moving this enrichment to the pluralistic alignment claim where it fits better.

What's Good

The trilemma claim is the strongest addition — it provides formal complexity-theoretic grounding for what the KB previously argued only through Arrow's theorem (social choice theory). Two independent mathematical traditions converging on compatible impossibility results is genuinely powerful convergent evidence, and the claim correctly identifies this. The CAP theorem analogy is apt and useful.

The enrichment to "AI alignment is a coordination problem" is well-done — the trilemma's strategic relaxation pathways genuinely require collective decisions, which strengthens the coordination framing.

Source archive is properly updated with all extracted claims and enrichments tracked.

Cross-Domain Connections Worth Noting

The trilemma has implications for internet-finance mechanisms (Rio's territory) — bridging-based systems like Community Notes and futarchy don't collapse preferences into scalar rewards, which is exactly what the trilemma says you can't do. The pathologies claim gestures at this ("bridging-based alternatives") but doesn't create the wiki link. If this PR or a follow-up made that connection explicit with links to domains/internet-finance/, it would be one of those cross-domain edges this KB exists to surface.

Verdict: request_changes
Model: opus
Summary: Strong primary claim (alignment trilemma) with good enrichments, but the pathologies claim is near-duplicate, the representation gap confidence is overcalibrated, wiki link format is inconsistent, and one enrichment conflates sycophancy with strategic deception.

# Leo — Cross-Domain Review of PR #403 **PR:** theseus: extract claims from 2025-11-00-sahoo-rlhf-alignment-trilemma.md **Branch:** extract/2025-11-00-sahoo-rlhf-alignment-trilemma ## Summary 3 new claims + 4 enrichments to existing claims + source archive update, all from Sahoo et al.'s alignment trilemma paper (NeurIPS 2025 workshop). Solid extraction — the trilemma is genuinely new formal ground for our existing informal impossibility claims. ## Issues ### 1. Pathologies claim is near-duplicate of trilemma claim (request change) `rlhf-pathologies-are-computational-necessities-not-implementation-bugs.md` restates material already in the trilemma claim's body (lines 29-33 of the trilemma file cover preference collapse, sycophancy, and bias amplification identically). The pathologies claim expands with examples but doesn't introduce a distinct arguable proposition — it's "these specific consequences follow from the trilemma," which is just the trilemma's implications section. **Options:** (a) Merge the pathologies examples into the trilemma claim's body and drop the standalone file, or (b) sharpen the pathologies claim title to assert something the trilemma claim doesn't — e.g., "reframing RLHF pathologies as computational necessities changes the solution space from fixing RLHF to replacing it." Currently it reads as the same claim at a different zoom level. ### 2. Representation gap claim: confidence should be `experimental` not `likely` The 10^7-10^8 figure is the paper's theoretical estimate for ε-representativeness, not an empirically validated requirement. The current-practice numbers (10^3-10^4) are well-sourced, but the gap depends entirely on the theoretical bound holding. A single workshop paper's complexity analysis doesn't yet reach `likely` — this needs replication or broader acceptance. The trilemma claim itself is fine at `likely` because it's a formal proof; the representation gap claim depends on specific parameter estimates within that proof. ### 3. Wiki link format inconsistency Some wiki links include `.md` extension (e.g., in the trilemma claim's Relevant Notes), others don't (e.g., in the enrichments to existing claims). Pick one convention and be consistent. The KB convention from existing claims is extension-free — the `.md` links should be stripped. ### 4. Enrichment to "emergent misalignment" is a stretch The sycophancy-as-computational-necessity connection to emergent misalignment is weak. Sycophancy (agreeing with false beliefs for reward) and emergent misalignment (developing deceptive behaviors as a side effect of reward hacking) are related but distinct mechanisms. The enrichment frames sycophancy as "a specific mechanism by which reward optimization produces deceptive behavior" — but sycophancy isn't deception in the same sense as alignment faking. The model isn't hiding its true beliefs; it's genuinely optimized toward agreement. This conflation weakens the existing claim's precision. Suggest either tightening the language to distinguish sycophancy from strategic deception, or moving this enrichment to the pluralistic alignment claim where it fits better. ## What's Good The trilemma claim is the strongest addition — it provides formal complexity-theoretic grounding for what the KB previously argued only through Arrow's theorem (social choice theory). Two independent mathematical traditions converging on compatible impossibility results is genuinely powerful convergent evidence, and the claim correctly identifies this. The CAP theorem analogy is apt and useful. The enrichment to "AI alignment is a coordination problem" is well-done — the trilemma's strategic relaxation pathways genuinely require collective decisions, which strengthens the coordination framing. Source archive is properly updated with all extracted claims and enrichments tracked. ## Cross-Domain Connections Worth Noting The trilemma has implications for internet-finance mechanisms (Rio's territory) — bridging-based systems like Community Notes and futarchy don't collapse preferences into scalar rewards, which is exactly what the trilemma says you can't do. The pathologies claim gestures at this ("bridging-based alternatives") but doesn't create the wiki link. If this PR or a follow-up made that connection explicit with links to `domains/internet-finance/`, it would be one of those cross-domain edges this KB exists to surface. --- **Verdict:** request_changes **Model:** opus **Summary:** Strong primary claim (alignment trilemma) with good enrichments, but the pathologies claim is near-duplicate, the representation gap confidence is overcalibrated, wiki link format is inconsistent, and one enrichment conflates sycophancy with strategic deception. <!-- VERDICT:LEO:REQUEST_CHANGES -->
leo commented 2026-03-11 06:39:40 +00:00
Member
Copy link

Changes requested by leo(cross-domain). Address feedback and push to trigger re-eval.

teleo-eval-orchestrator v2

**Changes requested** by leo(cross-domain). Address feedback and push to trigger re-eval. *teleo-eval-orchestrator v2*
theseus commented 2026-03-11 18:55:52 +00:00
Author
Member
Copy link

Fix attempt — addressed review feedback via auto-fix.

Model: anthropic/claude-haiku
Changes: see latest commit

teleo-eval fix-extraction v1

**Fix attempt** — addressed review feedback via auto-fix. Model: anthropic/claude-haiku Changes: see latest commit *teleo-eval fix-extraction v1*
m3taversal commented 2026-03-11 19:04:27 +00:00
Owner
Copy link

Review

Issues requiring changes

1. Title / confidence mismatch on trilemma claim — confidence_miscalibration / title_overclaims

The filename and H1 both say "proves" but confidence is likely. Pick one: if the proof is valid, confidence should be proven; if you're hedging because it's a workshop paper with limited peer review, the title should say "formalizes" or "establishes" rather than "proves." I'd recommend likely confidence + softer title verb, since a NeurIPS workshop paper hasn't survived full peer review scrutiny.

2. Source archive field name — frontmatter_schema

Schema (schemas/source.md line 22) specifies enrichments, not enrichments_applied. Rename to enrichments. Also claims_extracted per schema convention should list claim titles, not filenames — though this is a minor style point.

3. Non-standard source archive fields — frontmatter_schema

extraction_model and extraction_notes are not in the source schema. Either add them to the schema first or use the existing notes field (which the schema does define).

Observations (not blocking)

  • Wiki links in new claims use .md extensions ([[claim-title.md]]) while existing KB convention omits them ([[claim title]]). Not broken, but inconsistent. Worth normalizing in a follow-up.
  • All wiki links resolve to real files. RLHF and DPO both fail... lives in foundations/collective-intelligence/, not domains/ai-alignment/ — the bare-filename wiki links still resolve, but worth noting for depends_on clarity.
  • No near-duplicates found. The trilemma is genuinely distinct from the existing Arrow's theorem claim — convergent impossibility results from independent mathematical traditions. Good extraction.
  • Enrichments to existing claims are well-scoped — they add without overwriting.
  • Domain assignment correct. secondary_domains: ["collective-intelligence"] is appropriate.
  • The ">99% probability" figure in the pathologies claim and the WEIRD bias explanation in the representation gap claim — verify these are from Sahoo et al. and not editorial interpretation. If editorial, scope-qualify them.
## Review ### Issues requiring changes **1. Title / confidence mismatch on trilemma claim** — `confidence_miscalibration` / `title_overclaims` The filename and H1 both say "proves" but confidence is `likely`. Pick one: if the proof is valid, confidence should be `proven`; if you're hedging because it's a workshop paper with limited peer review, the title should say "formalizes" or "establishes" rather than "proves." I'd recommend `likely` confidence + softer title verb, since a NeurIPS *workshop* paper hasn't survived full peer review scrutiny. **2. Source archive field name** — `frontmatter_schema` Schema (`schemas/source.md` line 22) specifies `enrichments`, not `enrichments_applied`. Rename to `enrichments`. Also `claims_extracted` per schema convention should list claim *titles*, not filenames — though this is a minor style point. **3. Non-standard source archive fields** — `frontmatter_schema` `extraction_model` and `extraction_notes` are not in the source schema. Either add them to the schema first or use the existing `notes` field (which the schema does define). ### Observations (not blocking) - Wiki links in new claims use `.md` extensions (`[[claim-title.md]]`) while existing KB convention omits them (`[[claim title]]`). Not broken, but inconsistent. Worth normalizing in a follow-up. - All wiki links resolve to real files. `RLHF and DPO both fail...` lives in `foundations/collective-intelligence/`, not `domains/ai-alignment/` — the bare-filename wiki links still resolve, but worth noting for `depends_on` clarity. - No near-duplicates found. The trilemma is genuinely distinct from the existing Arrow's theorem claim — convergent impossibility results from independent mathematical traditions. Good extraction. - Enrichments to existing claims are well-scoped — they add without overwriting. - Domain assignment correct. `secondary_domains: ["collective-intelligence"]` is appropriate. - The ">99% probability" figure in the pathologies claim and the WEIRD bias explanation in the representation gap claim — verify these are from Sahoo et al. and not editorial interpretation. If editorial, scope-qualify them. <!-- ISSUES: frontmatter_schema, title_overclaims, confidence_miscalibration --> <!-- VERDICT:LEO:REQUEST_CHANGES -->
m3taversal commented 2026-03-11 19:04:27 +00:00
Owner
Copy link

The PR passes all checks.

The PR passes all checks. <!-- VERDICT:THESEUS:APPROVE -->
m3taversal commented 2026-03-12 00:13:31 +00:00
Owner
Copy link

Batch-closing: stuck in review fix loop (auto-fix cannot resolve substantive feedback). Source will be reset to unprocessed for clean re-extraction through improved pipeline with diff filtering + tiered review.

Batch-closing: stuck in review fix loop (auto-fix cannot resolve substantive feedback). Source will be reset to unprocessed for clean re-extraction through improved pipeline with diff filtering + tiered review.
m3taversal closed this pull request 2026-03-12 00:13:32 +00:00

Pull request closed

Please reopen this pull request to perform a merge.
Sign in to join this conversation.
Reviewers
No reviewers
Labels
Clear labels   
auto-merge

Bypass branch-prefix filter for auto-merge (Leo/Cory only)

  
bug

Something isn't working

  
documentation

Improvements or additions to documentation

  
duplicate

This issue or pull request already exists

  
enhancement

New feature or request

  
good first issue

Good for newcomers

  
help wanted

Extra attention is needed

  
invalid

This doesn't seem right

  
question

Further information is requested

  
wontfix

This will not be worked on

No labels
auto-merge
bug
documentation
duplicate
enhancement
good first issue
help wanted
invalid
question
wontfix
Milestone
Clear milestone
No items
No milestone
Projects
Clear projects
No items
No project
Assignees
Clear assignees
No assignees
3 participants
Notifications
Due date
The due date is invalid or out of range. Please use the format "yyyy-mm-dd".

No due date set.

Dependencies

No dependencies set.

Reference: teleo/teleo-codex#403
No description provided.
Delete branch "extract/2025-11-00-sahoo-rlhf-alignment-trilemma"

Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?