Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:07:54.567013Z
Paper Citation Record · LEDGER
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model
As of 17 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 5 inbound Pith citation observations for arXiv:2501.02790.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:59:20.189439Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T01:37:30.511368Z
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 52ba7fba-dc28-4045-8b69-1abab7b9054e · outbound
This paper cites Adding hops early in the boil (usually within the first 15 minutes) primarily contributes to the beer’s bitterness.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Adding hops early in the boil (usually within the first 15 minutes) primarily contributes to the beer’s bitterness
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T22:07:54.866830Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a4808866-602a-4262-885f-8183dba9a357 · outbound
This paper cites The bitterness level is moderate, and the hop flavors and some aromatic compounds are preserved better than in the early boil, thanks to the shorter exposure time.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model The bitterness level is moderate, and the hop flavors and some aromatic compounds are preserved better than in the early boil, thanks to the shorter exposure time
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T22:07:54.849886Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f8a7153d-d537-44ad-80cd-1803f0f73d12 · outbound
This paper cites This is because the shorter boiling time allows the volatile aromatic compounds to remain intact, while the alpha acids responsible for bitterness are less extracted.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model This is because the shorter boiling time allows the volatile aromatic compounds to remain intact, while the alpha acids responsible for bitterness are less extracted
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T22:07:54.832782Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c53aa61d-2c2f-467d-aabd-d7ecc2e0ebb0 · outbound
This paper cites This is done after the primary fermentation has completed, and the beer is transferred to a secondary fermenter or directly to the bottle/keg.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model This is done after the primary fermentation has completed, and the beer is transferred to a secondary fermenter or directly to the bottle/keg
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T22:07:54.815952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c11a862a-8a5f-4fc8-b73e-49575bc40e86 · outbound
This paper cites Spinach and Feta Egg Muffins.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Spinach and Feta Egg Muffins
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T22:07:54.798773Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e29cbc92-e1e1-44a7-bc90-a3cf0df62939 · outbound
This paper cites an unresolved cited work.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T22:07:54.696961Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ae4b4585-9915-4c02-88a2-e5cdf1012f28 · outbound
This paper cites an unresolved cited work.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T22:07:54.782680Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c5d1c61f-8afa-473e-a930-88a2e9e7b443 · outbound
This paper cites an unresolved cited work.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T22:07:54.764859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d217ee92-7bcc-44e6-909b-8d5c96c465e2 · outbound
This paper cites Stir until all the ingredients are evenly distributed.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Stir until all the ingredients are evenly distributed
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T22:07:54.747472Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a7003008-5cf3-4e7e-8df5-2692f73807c1 · outbound
This paper cites an unresolved cited work.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T22:07:54.730212Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d86e7d58-6d46-4edc-a883-1ca0aef06910 · outbound
This paper cites an unresolved cited work.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T22:07:54.713758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 82ee1389-56bd-40b2-aa7b-54c17ac78e0c · outbound
This paper cites an unresolved cited work.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Unresolved cited work
Reference 13
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T22:07:54.680867Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 351e48cd-4793-4374-84c4-bd526a8923d9 · outbound
This paper cites an unresolved cited work.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Unresolved cited work
Reference 14
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T22:07:54.663422Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 71260a24-a3bf-4002-af9f-1297cf6609bd · outbound
This paper cites The roots of the equation are: {roots[0]} and {roots[1]}.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model The roots of the equation are: {roots[0]} and {roots[1]}
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T22:07:54.646193Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e8176557-d097-4005-b745-46e67f6e0387 · outbound
This paper cites Global Statistics of All.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Global Statistics of All
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T22:07:54.628064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2eee8d5b-c2e1-402d-8d55-a6ea8292b7b7 · outbound
This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.
Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:07:54.481652Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation c7e0e76c-dfb0-42dd-a0ac-40850cb5cca2 · inbound
Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning cites this paper.
Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:37:31.014205Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 87939929-964a-4e5a-88ea-1058304cd6c7 · inbound
TGDPO: Harnessing Token-Level Reward Guidance for Enhancing Direct Preference Optimization cites this paper.
TGDPO: Harnessing Token-Level Reward Guidance for Enhancing Direct Preference Optimization Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:59:20.189439Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b5923323-4fcb-4b42-9458-093c65a4a7df · inbound
Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges cites this paper.
Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model
Reference 117
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T14:00:28.401522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 35917a05-ad3b-432d-881f-e8f9db0b75b6 · inbound
Reinforcing 3D Understanding in Point-VLMs via Geometric Reward Credit Assignment cites this paper.
Reinforcing 3D Understanding in Point-VLMs via Geometric Reward Credit Assignment Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T23:04:18.030277Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 26de573c-73ff-40fa-a7b8-64a60a72c502 · inbound
Proxy Reward Internalization and Mechanistic Exploitation: A Learned Precursor to Reward Hacking and Its Generalization cites this paper.
Proxy Reward Internalization and Mechanistic Exploitation: A Learned Precursor to Reward Hacking and Its Generalization Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model
Reference 151
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T01:37:30.512754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.