Paper Citation Record · LEDGER

Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 inbound Pith citation observations for arXiv:2506.06395.

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

pith.paper-citation-record.v1
2506.06395 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:35:24.315457Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T04:19:34.020533Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a7b0ad1c-dfe7-4e4a-adae-ca65f8b91856 · inbound

No Free Lunch: Rethinking Internal Feedback for LLM Reasoning cites this paper.

No Free Lunch: Rethinking Internal Feedback for LLM Reasoning Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T23:35:24.315457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfc426df-37f3-4055-877d-698b692486d3 · inbound

Maximizing Prefix-Confidence at Test-Time Efficiently Improves Mathematical Reasoning cites this paper.

Maximizing Prefix-Confidence at Test-Time Efficiently Improves Mathematical Reasoning Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T14:43:52.966250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f726fd13-53e2-436d-a482-265d307afd9b · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 280

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T00:02:24.731798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0b366e46-e0ea-4246-8b46-8beaf67c8df4 · inbound

Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision cites this paper.

Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-18T15:46:34.049081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0657594b-20a4-42e4-84e5-f1d2760997d2 · 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 Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-04T16:07:33.243783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c31a09d-140a-4ba0-b9d4-c89ed43e3847 · inbound

Self-Evolving Vision-Language Models for Image Quality Assessment via Voting and Ranking cites this paper.

Self-Evolving Vision-Language Models for Image Quality Assessment via Voting and Ranking Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-04T13:42:31.638150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb0f7f68-99bc-46f6-9fd1-a97d1f67acd1 · inbound

Breaking the Self-Confirming Loop: Diagnosing and Mitigating Systemic Reward Bias in Self-Rewarding RL cites this paper.

Breaking the Self-Confirming Loop: Diagnosing and Mitigating Systemic Reward Bias in Self-Rewarding RL Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T10:44:30.709604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80755571-d9f4-4a77-9222-4be56575688e · inbound

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning cites this paper.

CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:19.263434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a48785a-3065-4a6b-a1a4-f3a9b0ac43cd · inbound

Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards cites this paper.

Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-15T13:50:02.385698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7a5f517b-1ed4-42c9-ab8b-c8c24149ceb9 · inbound

Relationship-Centered Care: Relatedness and Responsible Design for Human Connections in Mental-Health Care cites this paper.

Relationship-Centered Care: Relatedness and Responsible Design for Human Connections in Mental-Health Care Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-14T20:22:12.729190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b8e06bf-4516-44e3-9dd5-59aa413d6e3f · inbound

Can LLMs Learn to Reason Robustly under Noisy Supervision? cites this paper.

Can LLMs Learn to Reason Robustly under Noisy Supervision? Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T17:08:01.328397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1b5a1f0a-dbe7-4c35-8427-3e4795804469 · inbound

HEALing Entropy Collapse: Enhancing Exploration in Few-Shot RLVR via Hybrid-Domain Entropy Dynamics Alignment cites this paper.

HEALing Entropy Collapse: Enhancing Exploration in Few-Shot RLVR via Hybrid-Domain Entropy Dynamics Alignment Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:23:37.520524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 136bdb10-f5df-4391-bbbf-5716b98d57f1 · inbound

Hallucinations Undermine Trust; Metacognition is a Way Forward cites this paper.

Hallucinations Undermine Trust; Metacognition is a Way Forward Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:56:07.150385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2225a65a-24bb-45d7-918a-647dc569ecf7 · inbound

Spatiotemporal Hidden-State Dynamics as a Signature of Internal Reasoning in Large Language Models cites this paper.

Spatiotemporal Hidden-State Dynamics as a Signature of Internal Reasoning in Large Language Models Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T16:21:08.878934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 91676cf1-799a-4ac2-8233-5761a453ac46 · inbound

Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs cites this paper.

Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:45:59.928030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 65dc5c60-d756-42d2-8f0d-482551526225 · inbound

Experience Sharing in Mutual Reinforcement Learning for Heterogeneous Language Models cites this paper.

Experience Sharing in Mutual Reinforcement Learning for Heterogeneous Language Models Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T04:00:54.981604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0adf9594-fec1-4beb-906f-ffcf2f486f1f · inbound

PDCR: Perception-Decomposed Confidence Reward for Vision-Language Reasoning cites this paper.

PDCR: Perception-Decomposed Confidence Reward for Vision-Language Reasoning Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:22:50.601594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0fb3c622-79d3-4020-b0d5-d46f3c71b144 · inbound

Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance cites this paper.

Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-15T03:19:43.052901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f4b05f7d-a7a9-483f-9ea8-8cd9c4ece2ea · inbound

Detecting and Mitigating the Correct-Answer Extinction Window in Test-Time Reinforcement Learning with Majority Voting cites this paper.

Detecting and Mitigating the Correct-Answer Extinction Window in Test-Time Reinforcement Learning with Majority Voting Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:23:06.927905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c1d205cb-439a-471a-a099-f5e14cd33be0 · inbound

Trust Region On-Policy Distillation cites this paper.

Trust Region On-Policy Distillation Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 80

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:56:13.714700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3fcabd54-4272-4f59-805a-86b1790d9ca2 · inbound

Smart Picks in the Dark: Towards Efficient RLVR for Reasoning via Tracing Metacognitive Pivots cites this paper.

Smart Picks in the Dark: Towards Efficient RLVR for Reasoning via Tracing Metacognitive Pivots Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:26:46.294521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 83ccfe0e-b653-4d2c-9dac-b0f2cfa1cb3c · inbound

GeoMin: Data-Efficient Semi-Supervised RLVR via Geometric Distribution Modeling cites this paper.

GeoMin: Data-Efficient Semi-Supervised RLVR via Geometric Distribution Modeling Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-02T06:06:40.756454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a1e595f4-6dc3-404d-8ca8-e0eea46b1270 · inbound

Architecture-Aware Reinforcement Learning Makes Sliding-Window Attention Competitive in Math Reasoning cites this paper.

Architecture-Aware Reinforcement Learning Makes Sliding-Window Attention Competitive in Math Reasoning Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-03T09:47:59.871201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bab38903-170f-4d40-b597-a461b8816476 · inbound

When Do Intrinsic Rewards Work for Code Reasoning? A Comprehensive Study cites this paper.

When Do Intrinsic Rewards Work for Code Reasoning? A Comprehensive Study Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T04:19:34.022356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.