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Paper Citation Record · LEDGER

Generalist Reward Models: Found Inside Large Language Models

As of 9 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 11 inbound Pith citation observations for arXiv:2506.23235.

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

pith.paper-citation-record.v1
2506.23235 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:57:31.438493Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:07:33.529325Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T23:07:27.285466Z

Reference resolution

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9e9ac82b-f32e-435b-ad4d-cb7a7d88312d · outbound

This paper cites an unresolved cited work.

Generalist Reward Models: Found Inside Large Language Models Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:57:33.731800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:30.288743Z digest=sha256:4961b6d03fd066b0d413b966c92cb11c599779f8d979bc9d14f80e7d3f322aed

Observation d6aff50c-16bf-4e5b-b60a-860349fc902e · outbound

This paper cites an unresolved cited work.

Generalist Reward Models: Found Inside Large Language Models Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:57:33.609996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:30.340039Z digest=sha256:b72309ffa4848199f0b086b4e0dab7ada6ccf12ecd1e420b14532db1bd9b8096

Observation f5c09ea7-d4db-4121-8cff-883fcf888922 · outbound

This paper cites YES” or “NO.

Generalist Reward Models: Found Inside Large Language Models YES” or “NO

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:57:33.507630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:30.420760Z digest=sha256:912b8168bc4f17629f7577671ae39c823f99413e21339616107f0e0e5371af00

Observation f745f784-c052-4687-b27e-50cd00ae5c58 · outbound

This paper cites an unresolved cited work.

Generalist Reward Models: Found Inside Large Language Models Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:57:33.370451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:30.493784Z digest=sha256:2579e7089240ccbaa9e6b2cc077742bf2925eebdc7e079186cca3f678005f22d

Observation 01fde5ba-a8e4-405f-9998-95ae89b709d8 · outbound

This paper cites an unresolved cited work.

Generalist Reward Models: Found Inside Large Language Models Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:57:33.261480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:30.670552Z digest=sha256:55133e7b94337c0b167a3fe377e2e6f02c0b47ce9413c020f1a0256d51015a2a

Observation f3d0da57-abc6-4fd0-80da-c36fbe8e0791 · outbound

This paper cites YES” or “NO.

Generalist Reward Models: Found Inside Large Language Models YES” or “NO

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:57:33.146128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:30.734457Z digest=sha256:17589c582e1196ce1bf792d95c765b9add911294707a5a4e67298014658f971b

Observation d52a7202-0354-498e-b9f6-b125909dd1f9 · outbound

This paper cites an unresolved cited work.

Generalist Reward Models: Found Inside Large Language Models Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:57:33.025023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:30.819922Z digest=sha256:22512b136e684de8d3322d728f0ac4f7cb5218c4e1b3971cc18a94a80206567d

Observation db6a2477-8f7c-4490-bd5c-f15ce9368af0 · outbound

This paper cites Figure 4: Prompt template of GenRM-Pairwise.

Generalist Reward Models: Found Inside Large Language Models Figure 4: Prompt template of GenRM-Pairwise

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:57:32.872859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:30.912049Z digest=sha256:3206e5777abe981b85598a5f371ca86c0a7bc92adac5a29e0393947c9cb31adf

Observation b137a385-e010-4f00-bbc8-c1b1694ef711 · outbound

This paper cites an unresolved cited work.

Generalist Reward Models: Found Inside Large Language Models Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:57:32.661723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:30.960775Z digest=sha256:b9f04a79e9b91d5d448b7118cb465fcecf6c77f8d7de9e6d2a168bf73927bc20

Observation e7bf130d-ef0a-4d3c-9249-52534100c4b9 · outbound

This paper cites an unresolved cited work.

Generalist Reward Models: Found Inside Large Language Models Unresolved cited work

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T21:57:31.034443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:57:31.034443Z digest=sha256:f32dd165d37fa5ddc6c8c745ef44d39ccb5474ced43f13281c60d25fe7ad476c

Observation f3699135-30a4-4e8b-abb4-7ff012d2d248 · outbound

This paper cites **Scoring Guide:** - **1-2:** Very Poor.

Generalist Reward Models: Found Inside Large Language Models **Scoring Guide:** - **1-2:** Very Poor

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:57:32.484508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:31.098643Z digest=sha256:9f2fa9cb8350a260b1d6429524585b90c4e0bde8a0265b4916ee56b9a4044c19

Observation 2c0920e7-41f7-40e0-9602-d72a37fada56 · outbound

This paper cites By Vieta’s formulas, we know: r1 + r2 + r3 = −a, r1r2 + r2r3 + r3r1 = a, r1r2r3 = −1.

Generalist Reward Models: Found Inside Large Language Models By Vieta’s formulas, we know: r1 + r2 + r3 = −a, r1r2 + r2r3 + r3r1 = a, r1r2r3 = −1

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:57:32.242903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:31.169721Z digest=sha256:53728566512c023db5437a16974ed49371ea10429ce839c72818ff30de7aea2c

Observation d6d87bec-aae0-4c0a-97e5-691068d6525f · outbound

This paper cites For a cubic polynomial x3 + px2 + qx + r = 0, the discriminant ∆ is given by: ∆ = 18abcd − 4b3d + b2c2 − 4ac3 − 27a2d2, where a = 1, b = a, c = a, and d = 1.

Generalist Reward Models: Found Inside Large Language Models For a cubic polynomial x3 + px2 + qx + r = 0, the discriminant ∆ is given by: ∆ = 18abcd − 4b3d + b2c2 − 4ac3 − 27a2d2, where a = 1, b = a, c = a, and d = 1

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:57:32.082431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:31.227139Z digest=sha256:31c117c65e9047015f635bb743f75f4ec4230fcdecf7a2528d2d146f6e2cdb45

Observation 267c47dd-99fa-42ac-85ef-d281ad345b08 · outbound

This paper cites So, we need to solve the inequality: a4 − 8a3 + 18a2 − 27 ≥ 0.

Generalist Reward Models: Found Inside Large Language Models So, we need to solve the inequality: a4 − 8a3 + 18a2 − 27 ≥ 0

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:57:31.894988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:31.299046Z digest=sha256:8416550942c6f23e74e95364d68c44f33910c2be3944604d1b3e2b38889cba06

Observation 9a2cd8c9-8639-4f50-bbc1-544b4c84a93b · outbound

This paper cites We can use numerical methods to find the roots of this polynomial.

Generalist Reward Models: Found Inside Large Language Models We can use numerical methods to find the roots of this polynomial

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:57:31.731633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:31.361047Z digest=sha256:797ada4072c5b3f52500973e048e6702a7257cb9be0782d6c6fe78f8350a1f78

Observation 161ad9a3-700e-4543-adb7-8a7f942431b8 · outbound

This paper cites an unresolved cited work.

Generalist Reward Models: Found Inside Large Language Models Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:57:31.585606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:57:31.438493Z digest=sha256:251bc9660bb0b32d207943555e9968c399685b7dc07df56f0597aa1f97429f11

Pith citing papers

Observation 3c4f3c73-7ac7-4134-b18f-4872dc27e914 · inbound

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence cites this paper.

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence Generalist Reward Models: Found Inside Large Language Models

Reference 252

Resolution
verified exact
arxiv_id, observed 2026-05-14T22:23:15.287388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-14T22:23:14.621091Z digest=sha256:496516846ebfa4788228177574002fcd35a525a3153546138ee4190859309e9c

Observation 6f1922a0-0415-4eae-b74f-083630c02ee7 · 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 Generalist Reward Models: Found Inside Large Language Models

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-04T16:07:33.529325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:07:33.529325Z digest=sha256:bfba7295135bcec6f3e72565a1c7f561c047549c57d37ac28a88f2beb6608855

Observation 8a908f5f-d786-4004-a0c4-5edab5a2b6e7 · inbound

Stabilizing Policy Optimization via Logits Convexity cites this paper.

Stabilizing Policy Optimization via Logits Convexity Generalist Reward Models: Found Inside Large Language Models

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-02T19:53:08.222944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:53:08.222944Z digest=sha256:2d484c1f8ab1c369a1382812ca5633260064d4e8d88ae9949105925e2cb569f0

Observation c1239ab4-b4ab-484e-8b29-6054d6e8fdf5 · inbound

Unleashing Implicit Rewards: Prefix-Value Learning for Distribution-Level Optimization cites this paper.

Unleashing Implicit Rewards: Prefix-Value Learning for Distribution-Level Optimization Generalist Reward Models: Found Inside Large Language Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:56:01.650291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T15:45:15.962965Z digest=sha256:15a6fd6610e15e895e45ef25866ba18bf225eed0474166bc5f081928bf5f8082

Observation df4cfeda-b72b-44dd-9a16-5f8ddec92d7c · inbound

Unleashing Implicit Rewards: Prefix-Value Learning for Distribution-Level Optimization cites this paper.

Unleashing Implicit Rewards: Prefix-Value Learning for Distribution-Level Optimization Generalist Reward Models: Found Inside Large Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-07-12T20:58:19.104482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T20:58:19.104482Z digest=sha256:bf6064b3736d007d736ceaee5da8a22087752fbef98d9f908a287fa24ab6a4eb

Observation c745f4bf-2eaa-4d89-b69b-d9221306ed03 · inbound

LC-ERD: Mining Latent Logic for Self-Evolving Reasoning via Consistency-Regulated Reward Decomposition cites this paper.

LC-ERD: Mining Latent Logic for Self-Evolving Reasoning via Consistency-Regulated Reward Decomposition Generalist Reward Models: Found Inside Large Language Models

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-06-30T18:45:00.055756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T18:44:14.878564Z digest=sha256:2ca4db2bd7fdd91a325ceb4cf356fa8e38203bc532fad4faa572d94511163cfd

Observation b9b50137-25e4-46c4-8d25-5ef029d8dfd0 · inbound

Directional Alignment Mitigates Reward Hacking in Reinforcement Learning for Language Models cites this paper.

Directional Alignment Mitigates Reward Hacking in Reinforcement Learning for Language Models Generalist Reward Models: Found Inside Large Language Models

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-06-30T12:24:39.632631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T12:22:49.708718Z digest=sha256:f596469456499f2506c151570c0f34843bbd9819e18b3d6deaa9da0a04cab398

Observation 2aabc5e7-18be-490b-bb3a-e5516fc54c19 · inbound

Trust Region On-Policy Distillation cites this paper.

Trust Region On-Policy Distillation Generalist Reward Models: Found Inside Large Language Models

Reference 179

Resolution
verified exact
arxiv_id, observed 2026-07-01T20:56:13.353106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T17:38:50.313305Z digest=sha256:27d6a60023f98470b65a13f74ceec1c639bfd9a2ee77c0503aa1df066380d7b9

Observation d4ae6d39-66a4-485e-90f0-90e8a8506301 · inbound

Momentum for Reasoning: Dense Intrinsic Signals in Policy Optimization cites this paper.

Momentum for Reasoning: Dense Intrinsic Signals in Policy Optimization Generalist Reward Models: Found Inside Large Language Models

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-07-02T23:07:27.287365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T18:26:22.701076Z digest=sha256:a0e6f3f6ae8cf431458c83578ee8650b4d6e7487e8020b832f8d6a85287c560d

Observation 29d8c3e8-4cfd-440f-9e19-d4774f3ea119 · inbound

REAR: Test-time Preference Realignment through Reward Decomposition cites this paper.

REAR: Test-time Preference Realignment through Reward Decomposition Generalist Reward Models: Found Inside Large Language Models

Reference 124

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T06:24:19.178680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-30T06:20:36.864229Z digest=sha256:a4335da8a1dbf35654a49a2dbb8ac7a37ff4b4d527ee39afe45c613f88aca8a8

Observation 3dd63f85-6a83-46b7-accf-0a054470812f · inbound

CAST: Game Solvers as Turn-Level Teachers for LLM Agents cites this paper.

CAST: Game Solvers as Turn-Level Teachers for LLM Agents Generalist Reward Models: Found Inside Large Language Models

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-01T02:58:29.404183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T02:58:29.404183Z digest=sha256:c2041d6d246eb8af02b06ed77a960b0af279defdcaf3dab3e8cffd0a6859480d