Paper Citation Record · LEDGER

Representation-Based Exploration for Language Models: From Test-Time to Post-Training

As of 13 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 10 inbound Pith citation observations for arXiv:2510.11686.

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

pith.paper-citation-record.v1
2510.11686 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T10:09:05.688277Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:39:40.961086Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:16:56.948632Z

Reference resolution

49 of 49 outbound references displayed

verified exact0
verified fuzzy0
unresolved48
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b79db884-03c4-410c-a06e-c586ff7d0c59 · outbound

This paper cites an unresolved cited work.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:05.406788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f85980d2-63eb-46cc-87e6-4a9ca443aefc · outbound

This paper cites Program Synthesis with Large Language Models.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Program Synthesis with Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.109898Z

Source-reported events for the cited work

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Observation b02aeed5-5e6d-4ec3-a9fd-2532a5403d52 · outbound

This paper cites Online Preference Alignment for Language Models via Count-based Exploration.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Online Preference Alignment for Language Models via Count-based Exploration

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.222940Z

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Observation 463e9e3b-2338-4e17-98df-71867a3154c2 · outbound

This paper cites InfAlign: Inference-aware language model alignment.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training InfAlign: Inference-aware language model alignment

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.325432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e65d4f4-0fa9-4cf3-969d-4b8fad1fc30a · outbound

This paper cites an unresolved cited work.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:05.543958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 926cde3f-18cb-45a0-b833-92284fb1fcdb · outbound

This paper cites PAD: Personalized Alignment of LLMs at Decoding-Time.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training PAD: Personalized Alignment of LLMs at Decoding-Time

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.528178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fa1d1e6-d42d-4e58-8ba4-68cd89d5d387 · outbound

This paper cites Enhancing diversity in large language models via determinantal point processes.arXiv preprint arXiv:2509.04784, 2025a.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Enhancing diversity in large language models via determinantal point processes.arXiv preprint arXiv:2509.04784, 2025a

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.586954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 232a33d4-98a9-4513-b3f7-66e92f757705 · outbound

This paper cites Uniform sampling for matrix approximation.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Uniform sampling for matrix approximation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.701918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ce1eab0-aff1-43ad-9c2c-3bb3c6e43ded · outbound

This paper cites Weight ensembling improves reasoning in language models.arXiv:2504.10478,.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Weight ensembling improves reasoning in language models.arXiv:2504.10478,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.753216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb676e2d-2c07-4cb0-ad95-199e248ce63b · outbound

This paper cites Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.866606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f146bee1-87d4-47a7-bdbf-e45a658605f7 · outbound

This paper cites Navigate the unknown: Enhancing llm reasoning with intrinsic motivation guided exploration.arXiv preprint arXiv:2505.17621,.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Navigate the unknown: Enhancing llm reasoning with intrinsic motivation guided exploration.arXiv preprint arXiv:2505.17621,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.936913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97269dc6-35f8-4512-a8c4-85965883311d · outbound

This paper cites Large-Scale Data Selection for Instruction Tuning.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Large-Scale Data Selection for Instruction Tuning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:02.113206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90838d63-31a2-46c7-8a5a-8ebd41642d03 · outbound

This paper cites Regularized Best-of-N Sampling with Minimum Bayes Risk Objective for Language Model Alignment.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Regularized Best-of-N Sampling with Minimum Bayes Risk Objective for Language Model Alignment

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:02.446650Z

Source-reported events for the cited work

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Observation 80061e44-3d5b-4f76-975c-ae0241157149 · outbound

This paper cites ARGS: Alignment as Reward-Guided Search.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training ARGS: Alignment as Reward-Guided Search

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:02.535591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 196d27bc-b522-4d0f-92b2-79ce5f46be03 · outbound

This paper cites Diverse Preference Optimization.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Diverse Preference Optimization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:02.661430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65341c38-834d-40f2-af35-ac56ad9d22fb · outbound

This paper cites Jointly Reinforcing Diversity and Quality in Language Model Generations.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Jointly Reinforcing Diversity and Quality in Language Model Generations

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:02.784967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 490f8c85-57a1-43fb-88ca-1c61f0020d16 · outbound

This paper cites Let's Verify Step by Step.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Let's Verify Step by Step

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:02.858946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8768ed37-c50e-4366-b06c-99eaf0815fb1 · outbound

This paper cites ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:02.979065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 136895b3-952e-41b6-8241-e64f54cc20fb · outbound

This paper cites Decoding-time Realignment of Language Models.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Decoding-time Realignment of Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:03.075477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aeada442-4a94-4af3-ab47-4efc1031ee6a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Proximal Policy Optimization Algorithms

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:03.215735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a1e0385-5950-46db-a390-5826abdc1213 · outbound

This paper cites e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:03.509893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f4bd61a-8b01-435a-a2d8-3e36ab7d83bc · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:03.708863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d08d0480-1de6-469f-b032-079c34fa1c10 · outbound

This paper cites HybridFlow: A Flexible and Efficient RLHF Framework.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training HybridFlow: A Flexible and Efficient RLHF Framework

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:03.780031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a313990a-e2cf-4fe1-8386-e1d359a077c2 · outbound

This paper cites Decoding-Time Language Model Alignment with Multiple Objectives.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Decoding-Time Language Model Alignment with Multiple Objectives

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:03.873616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 504fac42-bdc4-4eb3-97e4-d44016c45cf7 · outbound

This paper cites The invisible leash: Why rlvr may not escape its origin.arXiv preprint arXiv:2507.14843,.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training The invisible leash: Why rlvr may not escape its origin.arXiv preprint arXiv:2507.14843,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:03.992324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee320082-c0ca-4daf-9bb1-c229ce6aa84f · outbound

This paper cites Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:04.061180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ec0e46e-639f-4459-a353-d9fc20ce615e · outbound

This paper cites Formalizing Learning from Language Feedback with Provable Guarantees.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Formalizing Learning from Language Feedback with Provable Guarantees

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:04.124049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb2b05b5-f625-4fd5-bee9-2c5abec4ff16 · outbound

This paper cites Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:04.221022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 671555f6-4b85-40d5-8ae0-234b84091bd5 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:04.354294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d97fbf4-922a-42c9-976d-88763ceff4fa · outbound

This paper cites Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:04.463137Z

Source-reported events for the cited work

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Observation f00e0298-0149-4177-88b1-90d28a37585b · outbound

This paper cites Expo: Unlocking hard reasoning with self-explanation- guided reinforcement learning.arXiv preprint arXiv:2507.02834,.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Expo: Unlocking hard reasoning with self-explanation- guided reinforcement learning.arXiv preprint arXiv:2507.02834,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:04.603388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d292a63-4aa6-40c5-80df-e91d9fc64065 · outbound

This paper cites Most closely related to our work, Setlur et al.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Most closely related to our work, Setlur et al

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:04.694700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 265fcef4-fa43-420c-ad84-10b4275e9c7c · outbound

This paper cites breadth" (batch size) and “depth.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training breadth" (batch size) and “depth

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:04.846966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fce4406-4920-4fe3-bdc2-5af4915478fc · outbound

This paper cites Since the dataset does not come with any train or test splits, we use the full set of questions for our experiments.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Since the dataset does not come with any train or test splits, we use the full set of questions for our experiments

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:05.091913Z

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Observation db3ece86-d22c-42a7-b5f9-ed972f630f41 · outbound

This paper cites 1− n−c k n k # = 1 |D| |D|X i=1.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training 1− n−c k n k # = 1 |D| |D|X i=1

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:05.184426Z

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Observation 4d833705-21d9-4738-a7c2-5b930c08a1ac · outbound

This paper cites an unresolved cited work.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Unresolved cited work

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:05.306218Z

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Observation 739a1e3e-cd08-40e0-9283-e7ea6a0f8a89 · outbound

This paper cites an unresolved cited work.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Unresolved cited work

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:05.688277Z

Source-reported events for the cited work

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Observation 7810da19-7d76-4ce5-99b0-80de902e2f49 · outbound

This paper cites 5See also Arumugam and Griffiths (2025), which uses a pre-trained model to simulate posterior sampling in-context for multi-turn sequential decision making tasks.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training 5See also Arumugam and Griffiths (2025), which uses a pre-trained model to simulate posterior sampling in-context for multi-turn sequential decision making tasks

Reference 512

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:04.980774Z

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Observation 9c4b6958-efad-43b3-a733-470f9bcc0a3c · outbound

This paper cites Pass@K Policy Optimization: Solving Harder Reinforcement Learning Problems.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Pass@K Policy Optimization: Solving Harder Reinforcement Learning Problems

Reference 1992

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:03.938953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7093e53f-8790-4494-adc5-f70b9f0c8b2f · outbound

This paper cites The Llama 3 Herd of Models.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training The Llama 3 Herd of Models

Reference 2006

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.816289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69fd3b8d-2aa5-4606-b93a-117f4365fd7e · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Training Verifiers to Solve Math Word Problems

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.638862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0eb5adf9-106e-4306-9550-230e97de115d · outbound

This paper cites Phi-4 Technical Report.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Phi-4 Technical Report

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:00.796356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f0c4e45-d421-4efe-ba34-a2461a8ed359 · outbound

This paper cites Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:02.013031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8162654f-9f9b-44bc-8130-bdfa01ddf0bb · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Evaluating Large Language Models Trained on Code

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.459764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8c1a04d-130e-402d-a097-0545c2cb0b30 · outbound

This paper cites Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:03.372158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 715b425a-62a1-453e-ba41-0ef7d61e0ce5 · outbound

This paper cites Toward efficient exploration by large language model agents.arXiv preprint arXiv:2504.20997,.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Toward efficient exploration by large language model agents.arXiv preprint arXiv:2504.20997,

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:00.918533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23ca3af1-8764-442a-9128-d844f7ebc685 · outbound

This paper cites Mistral 7B.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Mistral 7B

Reference 2023

Resolution: malformed identifier; no resolver link, observed 2026-08-04T10:09:02.327154Z

Source-reported events for the cited work

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Observation 01876772-9818-43a0-bc5d-1d36c572f2cd · outbound

This paper cites Exploration by Random Network Distillation.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Exploration by Random Network Distillation

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.404089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8299430-4a49-47a9-a262-4b91bc6e1875 · outbound

This paper cites Anti-Concentrated Confidence Bonuses for Scalable Exploration.

Representation-Based Exploration for Language Models: From Test-Time to Post-Training Anti-Concentrated Confidence Bonuses for Scalable Exploration

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-04T10:09:01.013036Z

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Pith citing papers

Observation 060219b5-f3e1-4f7d-bc63-23d6c1e10395 · inbound

Provably avoiding over-optimization in Direct Preference Optimization without knowing the data distribution cites this paper.

Provably avoiding over-optimization in Direct Preference Optimization without knowing the data distribution Representation-Based Exploration for Language Models: From Test-Time to Post-Training

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-16T02:22:28.823656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7165350c-6e44-4731-a170-221bb6e1aab4 · inbound

Provably avoiding over-optimization in Direct Preference Optimization without knowing the data distribution cites this paper.

Provably avoiding over-optimization in Direct Preference Optimization without knowing the data distribution Representation-Based Exploration for Language Models: From Test-Time to Post-Training

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-16T02:22:28.823656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 83ffcf47-4606-4df4-9e25-4bf00c095336 · inbound

The Role of Generator Access in Autoregressive Post-Training cites this paper.

The Role of Generator Access in Autoregressive Post-Training Representation-Based Exploration for Language Models: From Test-Time to Post-Training

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-07-16T02:22:28.823656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0a6e9232-a3b5-4a36-8e5d-239df60335a2 · inbound

Data-dependent Exploration for Online Reinforcement Learning from Human Feedback cites this paper.

Data-dependent Exploration for Online Reinforcement Learning from Human Feedback Representation-Based Exploration for Language Models: From Test-Time to Post-Training

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-07-16T02:22:28.823656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dfdd086b-4452-41ad-96de-66c7666fd2de · inbound

Data-dependent Exploration for Online Reinforcement Learning from Human Feedback cites this paper.

Data-dependent Exploration for Online Reinforcement Learning from Human Feedback Representation-Based Exploration for Language Models: From Test-Time to Post-Training

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-16T02:22:28.823656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3f1deeeb-f615-4c04-ab0f-469b491d570d · inbound

The tractability landscape of diffusion alignment: regularization, rewards, and computational primitives cites this paper.

The tractability landscape of diffusion alignment: regularization, rewards, and computational primitives Representation-Based Exploration for Language Models: From Test-Time to Post-Training

Reference 30

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On Advantage Estimates for Max@K Policy Gradients cites this paper.

On Advantage Estimates for Max@K Policy Gradients Representation-Based Exploration for Language Models: From Test-Time to Post-Training

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-07-16T02:22:28.823656Z

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OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation cites this paper.

OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation Representation-Based Exploration for Language Models: From Test-Time to Post-Training

Reference 96

Resolution: metadata mismatch; arxiv_id, observed 2026-07-16T02:22:28.823656Z

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Observation 8554cc91-1b8d-49f8-8889-5cdc59e11cf5 · inbound

Partition, Prompt, Aggregate: Statistical Self-Consistency in Language Models cites this paper.

Partition, Prompt, Aggregate: Statistical Self-Consistency in Language Models Representation-Based Exploration for Language Models: From Test-Time to Post-Training

Reference 37

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Observation 58cd48d0-5f05-41ba-bab0-696d9cec0d80 · inbound

Ground-Truth Neighborhood Regularization for Reinforcement Learning Post-Training of Time Series Foundation Models cites this paper.

Ground-Truth Neighborhood Regularization for Reinforcement Learning Post-Training of Time Series Foundation Models Representation-Based Exploration for Language Models: From Test-Time to Post-Training

Reference 150

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