Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2504.16078.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T20:53:12.272937Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T22:46:53.836788Z
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 2cfbac60-fb60-47ee-984a-50b2db981f06 · inbound
Formalizing Learning from Language Feedback with Provable Guarantees cites this paper.
Formalizing Learning from Language Feedback with Provable Guarantees LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:39:19.638204Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4c83c026-a8b5-43f4-a14b-5811fa35562b · inbound
Input-Time Scaling: Adding Noise and Irrelevance into Less-Is-More Drastically Improves Reasoning Performance and Efficiency cites this paper.
Input-Time Scaling: Adding Noise and Irrelevance into Less-Is-More Drastically Improves Reasoning Performance and Efficiency LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T22:46:53.839788Z
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 e54cfaec-b1ea-4af7-98bb-e3953fd075ed · inbound
BioBlue: Systematic runaway-optimiser-like LLM failure modes on biologically and economically aligned AI safety benchmarks for LLMs with simplified observation format cites this paper.
BioBlue: Systematic runaway-optimiser-like LLM failure modes on biologically and economically aligned AI safety benchmarks for LLMs with simplified observation format LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:39:10.915427Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f3f4b64-5821-422e-aa76-1762997041e2 · inbound
Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation cites this paper.
Reward Modeling for Reinforcement Learning-Based LLM Reasoning: Design, Challenges, and Evaluation LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Reference 82
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T03:04:44.260995Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d15c79b-652e-4827-8e3f-80ee1f170659 · inbound
When Do We Need LLMs? A Diagnostic for Language-Driven Bandits cites this paper.
When Do We Need LLMs? A Diagnostic for Language-Driven Bandits LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Reference 41
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T00:25:51.144607Z
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 873fc6ac-4908-48fc-8314-28b34b99ae4a · inbound
Imaging-101: Benchmarking LLM Coding Agents on Scientific Computational Imaging cites this paper.
Imaging-101: Benchmarking LLM Coding Agents on Scientific Computational Imaging LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T09:17:00.467000Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c59bc3ed-e23b-4c20-98d8-65a1280885ea · inbound
STOCKTAKE: Measuring the Gap Between Perception and Action in LLM Agents with a Fair Oracle cites this paper.
STOCKTAKE: Measuring the Gap Between Perception and Action in LLM Agents with a Fair Oracle LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T04:42:06.208989Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ef0fa664-70fc-401c-a58f-fe810392e29e · inbound
AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization cites this paper.
AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T18:32:47.083166Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d9ba0ed0-8143-432e-bbba-0fb40675d299 · inbound
EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN cites this paper.
EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:53:12.272937Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.