Paper Citation Record · LEDGER

Reinforcement Learning for LLM Post-Training: A Survey

As of 22 August 2026, this Paper Citation Record lists 96 of 96 outbound references and 58 inbound Pith citation observations for arXiv:2407.16216.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2407.16216 v4

Coverage vector

measured 96 of 96 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-23T22:35:35.287039Z

measured 154 of 154 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 58 of 58 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:24:12.669701Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

96 of 96 outbound references displayed

verified exact6
verified fuzzy81
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

7
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 41ee95c0-ed31-4565-8582-4bec1964d30a · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Reinforcement Learning for LLM Post-Training: A Survey Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.479044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5ab86491-1f11-4173-8582-3f0e9a83c074 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for LLM Post-Training: A Survey Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-05-23T22:35:51.482409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d6f3456d-b78f-48fb-91fe-f27f3bdc1e3b · outbound

This paper cites Training a helpful and harmless assistant with reinforcement learning from human feedback.

Reinforcement Learning for LLM Post-Training: A Survey Training a helpful and harmless assistant with reinforcement learning from human feedback

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.486346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8bdeb67b-9621-411b-ac3d-f21b74ef9217 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for LLM Post-Training: A Survey Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-05-23T22:35:51.416492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a7510842-3eba-4869-9e23-ef019229ee74 · outbound

This paper cites The claude 3 model family: Opus, sonnet, haiku.

Reinforcement Learning for LLM Post-Training: A Survey The claude 3 model family: Opus, sonnet, haiku

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.475329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 710a6eb1-3f02-4ac1-b880-ee18e4d8020b · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Reinforcement Learning for LLM Post-Training: A Survey Gemini: A Family of Highly Capable Multimodal Models

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-23T22:35:50.304630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation df9518d0-8156-496d-a784-1b0110a74a29 · outbound

This paper cites Rlhf workflow: From reward modeling to online rlhf.

Reinforcement Learning for LLM Post-Training: A Survey Rlhf workflow: From reward modeling to online rlhf

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.378072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 19cb9fd8-1e69-4193-8b94-52e65e2b02ce · outbound

This paper cites Iterative preference learning from human feedback: Bridging theory and practice for rlhf under kl-constraint.

Reinforcement Learning for LLM Post-Training: A Survey Iterative preference learning from human feedback: Bridging theory and practice for rlhf under kl-constraint

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.397901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a5bedc3d-3223-4c19-9b81-8134f8cca61a · outbound

This paper cites Bowman, Zac Hatfield-Dodds, Ben Mann, Dario Amodei, Nicholas Joseph, Sam McCandlish, Tom Brown, and Jared Kaplan.

Reinforcement Learning for LLM Post-Training: A Survey Bowman, Zac Hatfield-Dodds, Ben Mann, Dario Amodei, Nicholas Joseph, Sam McCandlish, Tom Brown, and Jared Kaplan

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.639341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 737657c7-ad21-433e-883a-e52a6140e94e · outbound

This paper cites Rlaif: Scaling reinforcement learning from human feedback with ai feedback.

Reinforcement Learning for LLM Post-Training: A Survey Rlaif: Scaling reinforcement learning from human feedback with ai feedback

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.573067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5bad53b0-48e8-417a-b203-af6f6f171569 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for LLM Post-Training: A Survey Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-05-23T22:35:51.583731Z

Source-reported events for the cited work

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Observation f9169425-faf9-488b-a6c6-bb694d11a966 · outbound

This paper cites Manning, and Chelsea Finn.

Reinforcement Learning for LLM Post-Training: A Survey Manning, and Chelsea Finn

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.545251Z

Source-reported events for the cited work

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Observation 90bfbf4d-0a77-4b8f-ac5e-338a80697b01 · outbound

This paper cites Smaug: Fixing failure modes of preference optimisation with dpo-positive.

Reinforcement Learning for LLM Post-Training: A Survey Smaug: Fixing failure modes of preference optimisation with dpo-positive

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.539904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 12833e43-3931-4d83-814e-a1eb31bcf212 · outbound

This paper cites β-dpo: Direct preference optimization with dynamic β.

Reinforcement Learning for LLM Post-Training: A Survey β-dpo: Direct preference optimization with dynamic β

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.549126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 74acbde2-9219-46fb-bbbd-3f62361eb642 · outbound

This paper cites A general theoretical paradigm to understand learning from human preferences.

Reinforcement Learning for LLM Post-Training: A Survey A general theoretical paradigm to understand learning from human preferences

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.565905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ee29a6ea-2640-41c1-bd86-8919971c360d · outbound

This paper cites sdpo: Don’t use your data all at once.

Reinforcement Learning for LLM Post-Training: A Survey sdpo: Don’t use your data all at once

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.615981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f2cd99c0-c23d-4eae-bca1-fdd7cb9a4f4f · outbound

This paper cites From r to q∗: Your language model is secretly a q-function.

Reinforcement Learning for LLM Post-Training: A Survey From r to q∗: Your language model is secretly a q-function

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.693376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 37068e4e-f7d9-4b17-8516-1620c2cff80c · outbound

This paper cites Token-level direct preference optimization.

Reinforcement Learning for LLM Post-Training: A Survey Token-level direct preference optimization

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.493725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2e864275-507d-4ae1-9998-22abf3fcbc60 · outbound

This paper cites Self-rewarding language models.

Reinforcement Learning for LLM Post-Training: A Survey Self-rewarding language models

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.470156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5ab8bc47-8da8-4d3e-99f2-450e8633bd52 · outbound

This paper cites Some things are more cringe than others: Iterative preference optimization with the pairwise cringe loss.

Reinforcement Learning for LLM Post-Training: A Survey Some things are more cringe than others: Iterative preference optimization with the pairwise cringe loss

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.498202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 14e27ea6-a84f-445e-8675-73cda460eed1 · outbound

This paper cites Kto: Model alignment as prospect theoretic optimization.

Reinforcement Learning for LLM Post-Training: A Survey Kto: Model alignment as prospect theoretic optimization

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.531924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation eb2c37f0-9d2b-40a5-bde0-424cc1cc69a9 · outbound

This paper cites Offline regularised reinforcement learning for large language models alignment.

Reinforcement Learning for LLM Post-Training: A Survey Offline regularised reinforcement learning for large language models alignment

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.514400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2dc7bb51-2f68-439e-bc2a-7eec04505a71 · outbound

This paper cites Orpo: Monolithic preference optimization without reference model.

Reinforcement Learning for LLM Post-Training: A Survey Orpo: Monolithic preference optimization without reference model

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.507139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3a15b19e-901b-4da0-895f-1ff4d2d85cad · outbound

This paper cites Paft: A parallel training paradigm for effective llm fine-tuning.

Reinforcement Learning for LLM Post-Training: A Survey Paft: A parallel training paradigm for effective llm fine-tuning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.462277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2c05bf88-20f3-4fd2-854a-c08d4b8f7cc1 · outbound

This paper cites Disentangling length from quality in direct preference optimization.

Reinforcement Learning for LLM Post-Training: A Survey Disentangling length from quality in direct preference optimization

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.489672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cba4f34d-36e6-4e27-8479-93be185c267e · outbound

This paper cites Simpo: Simple preference optimization with a reference-free reward.

Reinforcement Learning for LLM Post-Training: A Survey Simpo: Simple preference optimization with a reference-free reward

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.524829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d7983a5b-7419-4b44-949b-68ce7060fac5 · outbound

This paper cites Back to basics: Revisiting reinforce style optimization for learning from human feedback in llms.

Reinforcement Learning for LLM Post-Training: A Survey Back to basics: Revisiting reinforce style optimization for learning from human feedback in llms

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.441352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ff98a8ae-3b4e-4d9f-aaf1-44c676d78743 · outbound

This paper cites Liu, and Xuanhui Wang.

Reinforcement Learning for LLM Post-Training: A Survey Liu, and Xuanhui Wang

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.559480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d4d7fde4-792c-4b0d-b6a0-3cddc5a58f94 · outbound

This paper cites Rrhf: Rank responses to align language models with human feedback without tears.

Reinforcement Learning for LLM Post-Training: A Survey Rrhf: Rank responses to align language models with human feedback without tears

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.580163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 11a31772-b1e4-4f5d-b2c1-99ac4f709805 · outbound

This paper cites Preference ranking optimization for human alignment.

Reinforcement Learning for LLM Post-Training: A Survey Preference ranking optimization for human alignment

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.503370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e0b4a298-5c89-452c-b199-8df7ba70b1a6 · outbound

This paper cites Negating negatives: Alignment without human positive samples via distributional dispreference optimization.

Reinforcement Learning for LLM Post-Training: A Survey Negating negatives: Alignment without human positive samples via distributional dispreference optimization

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.419438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e143ba21-90f9-4991-871d-9f73a25da5c9 · outbound

This paper cites Negative preference optimization: From catastrophic collapse to effective unlearning.

Reinforcement Learning for LLM Post-Training: A Survey Negative preference optimization: From catastrophic collapse to effective unlearning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.511504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation aea6477c-9704-42a0-b7ed-bd91fc5afd24 · outbound

This paper cites Contrastive preference optimization: Pushing the boundaries of llm performance in machine translation.

Reinforcement Learning for LLM Post-Training: A Survey Contrastive preference optimization: Pushing the boundaries of llm performance in machine translation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.536251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 81382c5c-effc-4216-bb54-8f9c4e55463e · outbound

This paper cites Mankowitz, Doina Precup, and Bilal Piot.

Reinforcement Learning for LLM Post-Training: A Survey Mankowitz, Doina Precup, and Bilal Piot

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.510618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a4f2e5ab-84a8-4f7b-8232-be7600e3cb30 · outbound

This paper cites A minimaximalist approach to reinforcement learning from human feedback.

Reinforcement Learning for LLM Post-Training: A Survey A minimaximalist approach to reinforcement learning from human feedback

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.415463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d32da5e4-3c98-43c7-ba72-639be4d84958 · outbound

This paper cites Direct nash optimization: Teaching language models to self-improve with general preferences.

Reinforcement Learning for LLM Post-Training: A Survey Direct nash optimization: Teaching language models to self-improve with general preferences

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.401392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a8b485f9-bed1-48bb-b1a1-db9f3f5814d1 · outbound

This paper cites Beyond reverse kl: Generalizing direct preference optimization with diverse divergence constraints.

Reinforcement Learning for LLM Post-Training: A Survey Beyond reverse kl: Generalizing direct preference optimization with diverse divergence constraints

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.408714Z

Source-reported events for the cited work

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Observation 7456c3d9-499d-4871-9292-2ecdbe5a8a2b · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for LLM Post-Training: A Survey Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-05-23T22:35:51.391681Z

Source-reported events for the cited work

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Observation a57386fa-1f0c-4055-976e-6be0bc487193 · outbound

This paper cites A markovian decision process.

Reinforcement Learning for LLM Post-Training: A Survey A markovian decision process

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.388440Z

Source-reported events for the cited work

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Observation 8ab25870-c9a6-46db-82e5-00fd6a328bc9 · outbound

This paper cites Hashimoto.

Reinforcement Learning for LLM Post-Training: A Survey Hashimoto

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.394727Z

Source-reported events for the cited work

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Observation a1778653-468c-4c57-ae85-77d0e4da3496 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

Reinforcement Learning for LLM Post-Training: A Survey Bleu: a method for automatic evaluation of machine translation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.412117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 32f7872b-193f-4e3c-b8f5-2b2cb02ff5ce · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Reinforcement Learning for LLM Post-Training: A Survey Rouge: A package for automatic evaluation of summaries

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.482168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7a2547ee-ce4c-427e-bdf1-793bd3cf4150 · outbound

This paper cites Weinberger, and Yoav Artzi.

Reinforcement Learning for LLM Post-Training: A Survey Weinberger, and Yoav Artzi

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.661237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 83c152fe-d6fe-4aa6-8797-04e68279cce9 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for LLM Post-Training: A Survey Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-05-23T22:35:51.429877Z

Source-reported events for the cited work

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Observation 696cf556-b69d-47cd-905b-9a70a9bd247f · outbound

This paper cites Truthfulqa: Measuring how models mimic human falsehoods.

Reinforcement Learning for LLM Post-Training: A Survey Truthfulqa: Measuring how models mimic human falsehoods

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.442972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4d46e208-6801-4766-a3ec-de799503b78d · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Reinforcement Learning for LLM Post-Training: A Survey Chain-of-thought prompting elicits reasoning in large language models

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.446993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 611436f5-ae08-47ce-84a4-aa10272c94d3 · outbound

This paper cites Ziegler, Ryan Lowe, Chelsea V oss, Alec Radford, Dario Amodei, and Paul Christiano.

Reinforcement Learning for LLM Post-Training: A Survey Ziegler, Ryan Lowe, Chelsea V oss, Alec Radford, Dario Amodei, and Paul Christiano

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.665586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b89e7f9e-2706-4d0b-b0f6-dac876fbcc1f · outbound

This paper cites Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, Eric Chu, Jonathan H.

Reinforcement Learning for LLM Post-Training: A Survey Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, Eric Chu, Jonathan H

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.576240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 48144c6b-97a2-42f1-a558-51791ce80eea · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Reinforcement Learning for LLM Post-Training: A Survey High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-05-23T22:35:50.309976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6e5b5ed8-83a9-4526-bca2-2fd5350c0a3b · outbound

This paper cites Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J.

Reinforcement Learning for LLM Post-Training: A Survey Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.444955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 985f1914-c302-4e1d-b75d-366da530af38 · outbound

This paper cites Liu, and Jialu Liu.

Reinforcement Learning for LLM Post-Training: A Survey Liu, and Jialu Liu

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.696964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ebebe5be-521a-4bce-bf94-a49137173aa8 · outbound

This paper cites Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study.

Reinforcement Learning for LLM Post-Training: A Survey Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-23T22:35:50.282923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 914132a8-46b6-498b-93ee-1e777a015ab2 · outbound

This paper cites Maas, Raymond E.

Reinforcement Learning for LLM Post-Training: A Survey Maas, Raymond E

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.689798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 44b9fd79-d89e-4ca1-88e4-5c4a81c67f8f · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Reinforcement Learning for LLM Post-Training: A Survey Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 55

Resolution: verified exact; local_arxiv, observed 2026-05-23T22:35:50.294514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c127a630-88c7-4e30-9455-117dd01e7e21 · outbound

This paper cites Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.

Reinforcement Learning for LLM Post-Training: A Survey Hellaswag: Can a machine really finish your sentence? In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.712970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6220a988-6323-437a-a3a2-8994ac19879a · outbound

This paper cites Kwok, Zhenguo Li, Adrian Weller, and Weiyang Liu.

Reinforcement Learning for LLM Post-Training: A Survey Kwok, Zhenguo Li, Adrian Weller, and Weiyang Liu

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.652034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 93e86d94-962d-42d4-91ad-ad6bb5319b60 · outbound

This paper cites Xing, Hao Zhang, Joseph E.

Reinforcement Learning for LLM Post-Training: A Survey Xing, Hao Zhang, Joseph E

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.671441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 45c694d0-ef68-4c86-b975-89963006acf4 · outbound

This paper cites Pythia: A suite for analyzing large language models across training and scaling.

Reinforcement Learning for LLM Post-Training: A Survey Pythia: A suite for analyzing large language models across training and scaling

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.679386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation af334596-b044-46de-a42a-9ed0357a83bd · outbound

This paper cites Solar 10.7b: Scaling large language models with simple yet effective depth up-scaling.

Reinforcement Learning for LLM Post-Training: A Survey Solar 10.7b: Scaling large language models with simple yet effective depth up-scaling

Reference 60

Resolution: malformed identifier; raw_fallback, observed 2026-05-23T22:35:51.619674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7dffecc0-3606-4704-8e5d-56b776ea295d · outbound

This paper cites Orca: Progressive learning from complex explanation traces of gpt-4.

Reinforcement Learning for LLM Post-Training: A Survey Orca: Progressive learning from complex explanation traces of gpt-4

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.605131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cbbc87f2-12e0-40f3-81a2-9b5a366cc81a · outbound

This paper cites Ultrafeedback: Boosting language models with high-quality feedback.

Reinforcement Learning for LLM Post-Training: A Survey Ultrafeedback: Boosting language models with high-quality feedback

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.590154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6cac6db5-fd88-47cc-8280-b276c08dc9aa · outbound

This paper cites Measuring massive multitask language understanding.

Reinforcement Learning for LLM Post-Training: A Survey Measuring massive multitask language understanding

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.593896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e9d142e5-78ac-4ab3-845a-ec23f0747172 · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale.

Reinforcement Learning for LLM Post-Training: A Survey Winogrande: An adversarial winograd schema challenge at scale

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.609644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bf26ad90-ca31-454c-9f01-ca8cd4f79f12 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Reinforcement Learning for LLM Post-Training: A Survey Training Verifiers to Solve Math Word Problems

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-05-23T22:35:50.288719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 737de695-d107-44c9-89d1-eac482791dbf · outbound

This paper cites Generalized preference optimization: A unified approach to offline alignment.

Reinforcement Learning for LLM Post-Training: A Survey Generalized preference optimization: A unified approach to offline alignment

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.570012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b3ea4c40-b1e4-47f9-9a82-ea6c2e86583e · outbound

This paper cites Language models are unsupervised multitask learners.

Reinforcement Learning for LLM Post-Training: A Survey Language models are unsupervised multitask learners

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.580449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7bb92faf-99cb-49ac-a7d1-4fb093f39379 · outbound

This paper cites Llama 2: Open foundation and fine-tuned chat models.

Reinforcement Learning for LLM Post-Training: A Survey Llama 2: Open foundation and fine-tuned chat models

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.587175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 829acdd5-5433-4a4f-bc7c-8e798de4b516 · outbound

This paper cites The cringe loss: Learning what language not to model.

Reinforcement Learning for LLM Post-Training: A Survey The cringe loss: Learning what language not to model

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.630359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d2973944-a7d3-47e5-adff-5e0316f35255 · outbound

This paper cites Hashimoto.

Reinforcement Learning for LLM Post-Training: A Survey Hashimoto

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.529270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 07ea3b54-dd38-4bb9-ab20-65e19538d55a · outbound

This paper cites Advances in prospect theory: Cumulative representation of uncertainty.

Reinforcement Learning for LLM Post-Training: A Survey Advances in prospect theory: Cumulative representation of uncertainty

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.526071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 66fabb02-424f-437d-9bf7-87525f861d18 · outbound

This paper cites Proximal policy optimization algorithms.

Reinforcement Learning for LLM Post-Training: A Survey Proximal policy optimization algorithms

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.532606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 577b2d2d-1ae5-46ed-8d3f-1497d9cb6209 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for LLM Post-Training: A Survey Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-05-23T22:35:51.633995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 07bff1ea-da89-472d-ad0b-613b07be387b · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Reinforcement Learning for LLM Post-Training: A Survey Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 74

Resolution: verified exact; local_arxiv, observed 2026-05-23T22:35:50.299816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1c6b788f-266b-496c-97aa-6397074e733c · outbound

This paper cites Phi-2: The surprising power of small language models.

Reinforcement Learning for LLM Post-Training: A Survey Phi-2: The surprising power of small language models

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.563796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f7ef9e94-119e-42f1-a00e-468bdeafab0f · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for LLM Post-Training: A Survey Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-05-23T22:35:51.514946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation daeb35c3-6af9-41c4-9bfc-1681de57d7b2 · outbound

This paper cites Instruction-following evaluation for large language models.

Reinforcement Learning for LLM Post-Training: A Survey Instruction-following evaluation for large language models

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.518764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a63075f8-1aa7-4c43-a0a0-a6a0848b2539 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Reinforcement Learning for LLM Post-Training: A Survey Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.545512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 17579027-2b4a-43c1-bcc2-7dcb0935f694 · outbound

This paper cites Gonzalez, and Ion Stoica.

Reinforcement Learning for LLM Post-Training: A Survey Gonzalez, and Ion Stoica

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.518033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3df9b7fd-5e9e-4321-a88c-f726d6c706ac · outbound

This paper cites Simple statistical gradient-following algorithms for connectionist reinforcement learning.

Reinforcement Learning for LLM Post-Training: A Survey Simple statistical gradient-following algorithms for connectionist reinforcement learning

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.683292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0d944cac-3c8d-46d5-a075-87e31d2ec18c · outbound

This paper cites Buy 4 REINFORCE samples, get a baseline for free!.

Reinforcement Learning for LLM Post-Training: A Survey Buy 4 REINFORCE samples, get a baseline for free!

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.552696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2db9056c-7483-4753-8b60-19302329c864 · outbound

This paper cites Learning to rank for information retrieval.

Reinforcement Learning for LLM Post-Training: A Survey Learning to rank for information retrieval

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.553126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5d0e78e9-0a98-4bc1-8f8f-ccdf8b8776a1 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for LLM Post-Training: A Survey Unresolved cited work

Reference 83

Resolution: unresolved; raw_fallback, observed 2026-05-23T22:35:51.642809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b00bca99-5099-4c51-b2f5-c087e9a0f940 · outbound

This paper cites Openassistant conversations – democratizing large language model alignment.

Reinforcement Learning for LLM Post-Training: A Survey Openassistant conversations – democratizing large language model alignment

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.528599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation caa32368-772c-4fac-aa0e-8d37c2064eb6 · outbound

This paper cites Hashimoto.

Reinforcement Learning for LLM Post-Training: A Survey Hashimoto

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.559788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f41a71fb-eece-4c83-bb8b-db9a8deef6e5 · outbound

This paper cites Secrets of rlhf in large language models part ii: Reward modeling.

Reinforcement Learning for LLM Post-Training: A Survey Secrets of rlhf in large language models part ii: Reward modeling

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.571733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 732b60fd-bad0-4dd5-b241-e2d2243d738d · outbound

This paper cites Safe rlhf: Safe reinforcement learning from human feedback.

Reinforcement Learning for LLM Post-Training: A Survey Safe rlhf: Safe reinforcement learning from human feedback

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.657844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a3466e86-ac7c-4a7d-a803-3cfa805308bf · outbound

This paper cites Lipton, and J.

Reinforcement Learning for LLM Post-Training: A Survey Lipton, and J

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.648279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9ead4ea7-08ef-4c83-b1c6-b5622e5e4d4a · outbound

This paper cites A paradigm shift in machine translation: Boosting translation performance of large language models.

Reinforcement Learning for LLM Post-Training: A Survey A paradigm shift in machine translation: Boosting translation performance of large language models

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.701061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 29ad9da9-968d-42cf-934d-f2077af82f7a · outbound

This paper cites On the limitations of the elo, real-world games are transitive, not additive.

Reinforcement Learning for LLM Post-Training: A Survey On the limitations of the elo, real-world games are transitive, not additive

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.705266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 35116a69-8d42-4971-b104-f0274d074a9c · outbound

This paper cites Self-play preference optimization for language model alignment.

Reinforcement Learning for LLM Post-Training: A Survey Self-play preference optimization for language model alignment

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.577157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e6375735-596d-49b2-b62b-63f99fa40c54 · outbound

This paper cites Schapire.

Reinforcement Learning for LLM Post-Training: A Survey Schapire

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.622936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e2eb508d-fac0-49e5-9c80-046ac23e41ea · outbound

This paper cites Llm-blender: Ensembling large language models with pairwise ranking and generative fusion.

Reinforcement Learning for LLM Post-Training: A Survey Llm-blender: Ensembling large language models with pairwise ranking and generative fusion

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.716609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a58d8c4c-8b7f-4c89-8fbe-e47710ed9aa2 · outbound

This paper cites Orca 2: Teaching small language models how to reason.

Reinforcement Learning for LLM Post-Training: A Survey Orca 2: Teaching small language models how to reason

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.521463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 10e9967c-47a8-4a89-a04e-dd069ca98ca6 · outbound

This paper cites On decoding strategies for neural text generators.

Reinforcement Learning for LLM Post-Training: A Survey On decoding strategies for neural text generators

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.501985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6892be44-c36d-4e92-b3c9-77c487ee1612 · outbound

This paper cites Insights into alignment: Evaluating dpo and its variants across multiple tasks.

Reinforcement Learning for LLM Post-Training: A Survey Insights into alignment: Evaluating dpo and its variants across multiple tasks

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.522881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 422cf210-88ee-448d-9e2c-acbc1f761e69 · outbound

This paper cites Is dpo superior to ppo for llm alignment? a comprehensive study.

Reinforcement Learning for LLM Post-Training: A Survey Is dpo superior to ppo for llm alignment? a comprehensive study

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-05-23T22:35:51.563056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation 3f4c7885-a7d7-4540-b853-7946b11876d2 · inbound

Language Models for Code Optimization: Survey, Challenges and Future Directions cites this paper.

Language Models for Code Optimization: Survey, Challenges and Future Directions Reinforcement Learning for LLM Post-Training: A Survey

Reference 140

Resolution: unresolved; no resolver link, observed 2026-08-10T22:34:34.886081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e77c8d6b-4819-4097-b062-3685465a125b · inbound

Many of Your DPOs are Secretly One: Attempting Unification Through Mutual Information cites this paper.

Many of Your DPOs are Secretly One: Attempting Unification Through Mutual Information Reinforcement Learning for LLM Post-Training: A Survey

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T22:32:56.529090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97047068-fd81-44ab-b96e-4ee8ee8ddf25 · inbound

Normative Evaluation of Large Language Models with Everyday Moral Dilemmas cites this paper.

Normative Evaluation of Large Language Models with Everyday Moral Dilemmas Reinforcement Learning for LLM Post-Training: A Survey

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T00:49:57.120759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36ea623a-0563-46d3-be3a-43262adaa47d · inbound

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment cites this paper.

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment Reinforcement Learning for LLM Post-Training: A Survey

Reference 223

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:12.669701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 473d809d-d83c-42f9-b01f-6af87fd5afa9 · inbound

Antidote: A Unified Framework for Mitigating LVLM Hallucinations in Counterfactual Presupposition and Object Perception cites this paper.

Antidote: A Unified Framework for Mitigating LVLM Hallucinations in Counterfactual Presupposition and Object Perception Reinforcement Learning for LLM Post-Training: A Survey

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T05:33:05.286073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a2585f5-4521-4310-88dd-15dae3ba40d3 · inbound

HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation cites this paper.

HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Reinforcement Learning for LLM Post-Training: A Survey

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T05:18:07.033884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89d9599f-d45c-407d-9ad9-74df626f7c6b · inbound

A Survey on Progress in LLM Alignment from the Perspective of Reward Design cites this paper.

A Survey on Progress in LLM Alignment from the Perspective of Reward Design Reinforcement Learning for LLM Post-Training: A Survey

Reference 28

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Observation cfef34eb-55a5-4923-b85b-7055b566bcf5 · inbound

Ethics and Persuasion in Reinforcement Learning from Human Feedback: A Procedural Rhetorical Approach cites this paper.

Ethics and Persuasion in Reinforcement Learning from Human Feedback: A Procedural Rhetorical Approach Reinforcement Learning for LLM Post-Training: A Survey

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T21:30:36.266375Z

Source-reported events for the cited work

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Observation b539ee6f-cebb-4b93-93e9-627b6d143fdb · inbound

A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO cites this paper.

A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO Reinforcement Learning for LLM Post-Training: A Survey

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T15:19:09.406012Z

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Observation 01410d90-fb2e-45c3-b15d-3c1fdd2cf1dd · inbound

Advancing LLM Safe Alignment with Safety Representation Ranking cites this paper.

Advancing LLM Safe Alignment with Safety Representation Ranking Reinforcement Learning for LLM Post-Training: A Survey

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:18.318170Z

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Unavailable: canonical work link unavailable.

Observation ed33eb3c-588d-40f4-b5d4-4f68de34dea2 · inbound

Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval cites this paper.

Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval Reinforcement Learning for LLM Post-Training: A Survey

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:48.734701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb5bcec9-0d8c-4b71-a4a5-f9d5840f3113 · inbound

Multi-Domain Explainability of Preferences cites this paper.

Multi-Domain Explainability of Preferences Reinforcement Learning for LLM Post-Training: A Survey

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T14:05:12.907001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac9e2e24-ee35-4fd7-b56a-a86ae8a39575 · inbound

Unveiling Instruction-Specific Neurons & Experts: An Analytical Framework for LLM's Instruction-Following Capabilities cites this paper.

Unveiling Instruction-Specific Neurons & Experts: An Analytical Framework for LLM's Instruction-Following Capabilities Reinforcement Learning for LLM Post-Training: A Survey

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:23.597483Z

Source-reported events for the cited work

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Observation b90d553c-2bc3-4b50-a060-c07269eedf3a · inbound

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction cites this paper.

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction Reinforcement Learning for LLM Post-Training: A Survey

Reference 41

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T11:37:16.014516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 22c6f668-2bb8-4441-afa9-2db16d208578 · inbound

Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences cites this paper.

Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences Reinforcement Learning for LLM Post-Training: A Survey

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T11:26:58.366027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d507ed32-0dc3-4897-99f5-69487eea9eca · inbound

Brevity is the soul of sustainability: Characterizing LLM response lengths cites this paper.

Brevity is the soul of sustainability: Characterizing LLM response lengths Reinforcement Learning for LLM Post-Training: A Survey

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T05:09:11.331229Z

Source-reported events for the cited work

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Observation 41321313-bb77-41b8-856f-84ad7fcbe144 · inbound

Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Model cites this paper.

Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Model Reinforcement Learning for LLM Post-Training: A Survey

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T05:03:15.250044Z

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Unavailable: canonical work link unavailable.

Observation 4bb4783a-b6b6-4dad-bb60-51766d8a175a · inbound

Exploring the Secondary Risks of Large Language Models cites this paper.

Exploring the Secondary Risks of Large Language Models Reinforcement Learning for LLM Post-Training: A Survey

Reference 47

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T09:42:13.985529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 48b5883c-1205-4056-9750-5aee35549958 · inbound

Simulating multiple human perspectives in socio-ecological systems using large language models cites this paper.

Simulating multiple human perspectives in socio-ecological systems using large language models Reinforcement Learning for LLM Post-Training: A Survey

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T18:22:43.299476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba916c9f-9c62-437c-9f14-46bee33a9acb · inbound

CTR-Driven Ad Text Generation via Online Feedback Preference Optimization cites this paper.

CTR-Driven Ad Text Generation via Online Feedback Preference Optimization Reinforcement Learning for LLM Post-Training: A Survey

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T13:48:46.717418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d5338f5-e98c-4264-b1fd-dbe29fbddc1b · inbound

An Explainable Emotion Alignment Framework for LLM-Empowered Agent in Metaverse Service Ecosystem cites this paper.

An Explainable Emotion Alignment Framework for LLM-Empowered Agent in Metaverse Service Ecosystem Reinforcement Learning for LLM Post-Training: A Survey

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T11:53:17.754032Z

Source-reported events for the cited work

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Observation e3f38a03-98a7-4fcc-8e31-0856c86913a3 · inbound

Enhancing Small LLM Alignment through Margin-Based Objective Modifications under Resource Constraints cites this paper.

Enhancing Small LLM Alignment through Margin-Based Objective Modifications under Resource Constraints Reinforcement Learning for LLM Post-Training: A Survey

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T21:33:14.784455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85a753f9-6bfc-45ea-99b9-89638003be12 · inbound

A Survey on Training-free Alignment of Large Language Models cites this paper.

A Survey on Training-free Alignment of Large Language Models Reinforcement Learning for LLM Post-Training: A Survey

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:48.405513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebd692bf-faeb-40d8-9d2e-c6ff0bde5d3a · inbound

EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention cites this paper.

EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention Reinforcement Learning for LLM Post-Training: A Survey

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-05-18T20:56:51.816772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5f5c0311-173e-4dcc-b796-221408854dff · inbound

Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning cites this paper.

Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning Reinforcement Learning for LLM Post-Training: A Survey

Reference 52

Resolution: metadata mismatch; local_arxiv, observed 2026-05-18T20:41:50.436344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fd962b78-169e-4c63-8873-44cb2333d49d · inbound

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey cites this paper.

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Reinforcement Learning for LLM Post-Training: A Survey

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-05-18T19:21:48.376249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cf9f655d-a984-48d5-a5e7-b7d55157347a · inbound

A Comprehensive Survey on Trustworthiness in Reasoning with Large Language Models cites this paper.

A Comprehensive Survey on Trustworthiness in Reasoning with Large Language Models Reinforcement Learning for LLM Post-Training: A Survey

Reference 273

Resolution: unresolved; no resolver link, observed 2026-08-05T10:39:08.244079Z

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Observation e6b7f581-ab53-4d4e-a416-17ebd7aa179b · inbound

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial cites this paper.

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial Reinforcement Learning for LLM Post-Training: A Survey

Reference 265

Resolution: unresolved; no resolver link, observed 2026-08-05T04:50:32.523428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a15aba6-4d84-491b-bcb5-292e9565c697 · inbound

EPT Benchmark: Evaluation of Persian Trustworthiness in Large Language Models cites this paper.

EPT Benchmark: Evaluation of Persian Trustworthiness in Large Language Models Reinforcement Learning for LLM Post-Training: A Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T23:03:16.345319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df2adc50-b14f-4bd0-b9ea-a23274a516e8 · inbound

Query Expansion in the Age of Pre-trained and Large Language Models: A Comprehensive Survey cites this paper.

Query Expansion in the Age of Pre-trained and Large Language Models: A Comprehensive Survey Reinforcement Learning for LLM Post-Training: A Survey

Reference 110

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:11:42.974325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f6300611-2eb1-4a5e-a01d-40ed2a7fe2ec · inbound

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle cites this paper.

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle Reinforcement Learning for LLM Post-Training: A Survey

Reference 178

Resolution: unresolved; no resolver link, observed 2026-08-04T16:07:43.117616Z

Source-reported events for the cited work

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Observation 2b16c4e7-1b7c-4756-b793-777bda1359ce · inbound

SCOPE-RL: Stable and Quantitative Control of Policy Entropy in RL Post-Training cites this paper.

SCOPE-RL: Stable and Quantitative Control of Policy Entropy in RL Post-Training Reinforcement Learning for LLM Post-Training: A Survey

Reference 19

Resolution: metadata mismatch; local_arxiv, observed 2026-05-21T20:30:35.472865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1bfb6bdd-e510-45ea-b57f-d08bcbf58d1a · inbound

Voting with the Graph: Stable RLAIF via Topological Consistency Maximization cites this paper.

Voting with the Graph: Stable RLAIF via Topological Consistency Maximization Reinforcement Learning for LLM Post-Training: A Survey

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T09:28:13.001684Z

Source-reported events for the cited work

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Observation 206d97fe-d9ff-4a62-b3a1-b31282853cbe · inbound

Maximizing the efficiency of human feedback in AI alignment: a comparative analysis cites this paper.

Maximizing the efficiency of human feedback in AI alignment: a comparative analysis Reinforcement Learning for LLM Post-Training: A Survey

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T22:02:16.789125Z

Source-reported events for the cited work

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Observation ee8de5cb-22a3-44e6-a3c6-92adee7be1f8 · inbound

RACC: Representation-Aware Coverage Criteria for LLM Safety Testing cites this paper.

RACC: Representation-Aware Coverage Criteria for LLM Safety Testing Reinforcement Learning for LLM Post-Training: A Survey

Reference 51

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T08:17:36.555589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 57d1d6d9-8bba-4db0-b197-cc43eed7a2ad · inbound

Safety Alignment as Continual Learning: Mitigating the Alignment Tax via Orthogonal Gradient Projection cites this paper.

Safety Alignment as Continual Learning: Mitigating the Alignment Tax via Orthogonal Gradient Projection Reinforcement Learning for LLM Post-Training: A Survey

Reference 22

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T06:40:41.730258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 92febfba-be07-4bce-956e-4459d2f6ea71 · inbound

VC-Soup: Value-Consistency Guided Multi-Value Alignment for Large Language Models cites this paper.

VC-Soup: Value-Consistency Guided Multi-Value Alignment for Large Language Models Reinforcement Learning for LLM Post-Training: A Survey

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-05-15T09:39:54.359255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a87cf072-c53d-482d-9bf8-bd7207b29052 · inbound

The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training cites this paper.

The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training Reinforcement Learning for LLM Post-Training: A Survey

Reference 61

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T00:45:50.664592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b479ae6a-3f9f-4648-b20e-7e70fce63411 · inbound

Mobile GUI Agent Privacy Personalization with Trajectory Induced Preference Optimization cites this paper.

Mobile GUI Agent Privacy Personalization with Trajectory Induced Preference Optimization Reinforcement Learning for LLM Post-Training: A Survey

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-11T09:11:01.113709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 07619aec-be4c-422f-9420-92393b1334c8 · inbound

ProjLens: Unveiling the Role of Projectors in Multimodal Model Safety cites this paper.

ProjLens: Unveiling the Role of Projectors in Multimodal Model Safety Reinforcement Learning for LLM Post-Training: A Survey

Reference 37

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T12:46:05.553273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ad446046-50cc-4b8d-aaff-a5c5998ef8af · inbound

Pref-CTRL: Preference Driven LLM Alignment using Representation Editing cites this paper.

Pref-CTRL: Preference Driven LLM Alignment using Representation Editing Reinforcement Learning for LLM Post-Training: A Survey

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-05-11T21:11:19.342574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b5582d48-55c7-485b-9d8f-d0866a6e76b0 · inbound

Generating Place-Based Compromises Between Two Points of View cites this paper.

Generating Place-Based Compromises Between Two Points of View Reinforcement Learning for LLM Post-Training: A Survey

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-05-11T22:01:12.088276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 70210b30-9bb9-4993-a0ae-25a3c5d1a2e2 · inbound

Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.

Rethinking Agentic Reinforcement Learning In Large Language Models Reinforcement Learning for LLM Post-Training: A Survey

Reference 95

Resolution: verified exact; local_arxiv, observed 2026-05-12T10:21:29.964715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7d51e331-406f-4c13-9633-1e0b2752d58f · inbound

Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.

Rethinking Agentic Reinforcement Learning In Large Language Models Reinforcement Learning for LLM Post-Training: A Survey

Reference 95

Resolution: verified exact; local_arxiv, observed 2026-05-11T22:11:16.721393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9e58f133-85e0-40f4-b5a1-a9d462a264cd · inbound

Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.

Rethinking Agentic Reinforcement Learning In Large Language Models Reinforcement Learning for LLM Post-Training: A Survey

Reference 95

Resolution: verified exact; local_arxiv, observed 2026-05-19T17:02:40.688757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8cb754df-3e9a-48c1-9039-97b4dcbdc9ff · inbound

Stable-GFlowNet: Toward Diverse and Robust LLM Red-Teaming via Contrastive Trajectory Balance cites this paper.

Stable-GFlowNet: Toward Diverse and Robust LLM Red-Teaming via Contrastive Trajectory Balance Reinforcement Learning for LLM Post-Training: A Survey

Reference 9

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T15:41:17.804578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2045f3d6-b30b-407c-adac-2243f11ef719 · inbound

Agents Should Replace Narrow Predictive AI as the Orchestrator in 6G AI-RAN cites this paper.

Agents Should Replace Narrow Predictive AI as the Orchestrator in 6G AI-RAN Reinforcement Learning for LLM Post-Training: A Survey

Reference 45

Resolution: metadata mismatch; local_arxiv, observed 2026-05-13T02:17:06.980568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ebaa50f6-de7e-4137-8a96-7d14b955712b · inbound

UNIPO: Unified Interactive Visual Explanation for RL Fine-Tuning Policy Optimization cites this paper.

UNIPO: Unified Interactive Visual Explanation for RL Fine-Tuning Policy Optimization Reinforcement Learning for LLM Post-Training: A Survey

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-13T01:42:03.971815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a5d940f6-bc0f-45d8-9b48-614becafa94a · inbound

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning cites this paper.

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning Reinforcement Learning for LLM Post-Training: A Survey

Reference 73

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T21:52:48.235735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 514183ef-2b4a-4335-a865-9861bc6f4aa6 · inbound

ReCrit: Transition-Aware Reinforcement Learning for Scientific Critic Reasoning cites this paper.

ReCrit: Transition-Aware Reinforcement Learning for Scientific Critic Reasoning Reinforcement Learning for LLM Post-Training: A Survey

Reference 37

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T22:53:49.325337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1970e252-73e9-4025-abff-429e5b4c6713 · inbound

DOG-DPO:Dynamic Optimization in Geometry for Safety Alignment cites this paper.

DOG-DPO:Dynamic Optimization in Geometry for Safety Alignment Reinforcement Learning for LLM Post-Training: A Survey

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T12:06:56.031254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f6851d24-0f0d-4dbb-9124-28228106628e · inbound

Reward-Free Code Alignment from Pretrained or Fine-Tuned LLM: Unpacking the Trade-offs for Code Generation cites this paper.

Reward-Free Code Alignment from Pretrained or Fine-Tuned LLM: Unpacking the Trade-offs for Code Generation Reinforcement Learning for LLM Post-Training: A Survey

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-06-30T08:34:26.678705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a7acfd67-0f89-4f61-9688-2203b6f2ddcd · inbound

Training Therapeutic Judges and Multi-Agent Systems for Human-Aligned Mental Health Support cites this paper.

Training Therapeutic Judges and Multi-Agent Systems for Human-Aligned Mental Health Support Reinforcement Learning for LLM Post-Training: A Survey

Reference 95

Resolution: verified exact; local_arxiv, observed 2026-07-01T12:35:43.844499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8da3d815-7164-449f-9afb-35f55a83bc06 · inbound

Meta-Learning Preferences for Multilingual LLM Alignment cites this paper.

Meta-Learning Preferences for Multilingual LLM Alignment Reinforcement Learning for LLM Post-Training: A Survey

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.410995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59a1edaa-924c-4831-a5be-ff2c11c0bace · inbound

Sound Probabilistic Safety Bounds for Large Language Models cites this paper.

Sound Probabilistic Safety Bounds for Large Language Models Reinforcement Learning for LLM Post-Training: A Survey

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T10:22:41.813908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6cadd64-ae02-4da7-8972-71698e65181d · inbound

On-Policy Distillation for LLM Safety: A Routing Approach to Template-Robust Realignment cites this paper.

On-Policy Distillation for LLM Safety: A Routing Approach to Template-Robust Realignment Reinforcement Learning for LLM Post-Training: A Survey

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-30T11:44:36.074744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd7bca3c-28f0-40dd-ab7b-1af6eb095fa4 · inbound

Cleo: A Transparent and Controllable Chatbot for Conversational Commerce cites this paper.

Cleo: A Transparent and Controllable Chatbot for Conversational Commerce Reinforcement Learning for LLM Post-Training: A Survey

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:36:33.069090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5153a63-dc2e-437c-9e86-d9e9f9d13f4f · inbound

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning cites this paper.

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning Reinforcement Learning for LLM Post-Training: A Survey

Reference 146

Resolution: unresolved; no resolver link, observed 2026-08-15T14:17:57.024485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.