Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2503.21248.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T05:17:18.385882Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T12:15:01.137692Z
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 1a622c17-1c75-40b4-9ecb-f3448cf8d2a0 · inbound
From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review cites this paper.
From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 235
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T02:57:38.190904Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5f454d90-f8c8-4364-9ffb-00b377deb460 · inbound
IDRBench: Understanding the Capability of Large Language Models on Interdisciplinary Research cites this paper.
IDRBench: Understanding the Capability of Large Language Models on Interdisciplinary Research ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T03:52:01.581385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d5f29e90-b949-46ec-9c5c-79d65cf60fb8 · inbound
FIRE-Bench: Evaluating AI Agents on the Rediscovery of Scientific Insights cites this paper.
FIRE-Bench: Evaluating AI Agents on the Rediscovery of Scientific Insights ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T05:17:18.385882Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 87d68fee-abb4-4001-ae3f-6ece1f560ad4 · inbound
Can Large Language Models Derive New Knowledge? A Dynamic Benchmark for Biological Knowledge Discovery cites this paper.
Can Large Language Models Derive New Knowledge? A Dynamic Benchmark for Biological Knowledge Discovery ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T02:57:46.930452Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c836fe18-46e3-40a0-a902-a9541aab91c0 · inbound
AI scientists produce results without reasoning scientifically cites this paper.
AI scientists produce results without reasoning scientifically ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 9
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T12:16:06.789382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6e5068c3-ca03-403c-95f1-78352ef8f733 · inbound
AstroAlertBench: Evaluating the Accuracy, Reasoning, and Honesty of Multimodal LLMs in Astronomical Classification cites this paper.
AstroAlertBench: Evaluating the Accuracy, Reasoning, and Honesty of Multimodal LLMs in Astronomical Classification ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 6
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-11T21:31:13.776475Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c412b56e-455c-434d-a41d-c14083931d31 · inbound
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI cites this paper.
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 56
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T08:21:25.167029Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a985dfca-1072-4802-a6a1-9063a0c4f531 · inbound
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI cites this paper.
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 58
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T13:25:46.055254Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c7f875f8-afcb-4b52-b7bb-cccf4226276b · inbound
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI cites this paper.
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T17:14:49.310598Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 221c4c7c-b92b-4040-b84f-f23b649768d4 · inbound
LEAP: Trajectory-Level Evaluation of LLMs in Iterative Scientific Design cites this paper.
LEAP: Trajectory-Level Evaluation of LLMs in Iterative Scientific Design ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T15:52:38.068813Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7cdf9a01-c210-4718-b773-a5d5abdedb0a · inbound
Scientific reasoning does not reliably translate into scientific forecasting in frontier AI cites this paper.
Scientific reasoning does not reliably translate into scientific forecasting in frontier AI ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:21:07.442521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 11219177-21d5-4887-b9c5-be5225a21935 · inbound
Scientific reasoning does not reliably translate into scientific forecasting in frontier AI cites this paper.
Scientific reasoning does not reliably translate into scientific forecasting in frontier AI ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T13:31:44.953243Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fcbbcd39-7d85-45c5-90c6-17ffaa4d8414 · inbound
AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery cites this paper.
AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 56
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T04:50:21.922451Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f8b623b0-94f6-45fb-b711-c763fca21614 · inbound
ScientistOne: Towards Human-Level Autonomous Research via Chain-of-Evidence cites this paper.
ScientistOne: Towards Human-Level Autonomous Research via Chain-of-Evidence ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T21:23:59.088553Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 772902d4-0768-428d-a06f-4b1ddf8fb818 · inbound
Matter to Mechanism: A Benchmark for AI Co-Scientists in Materials and Battery Research cites this paper.
Matter to Mechanism: A Benchmark for AI Co-Scientists in Materials and Battery Research ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T12:12:07.898907Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ca7970c7-2ef8-4d1f-b82a-3c2d6b8fce71 · inbound
DN-Hypo-Pipeline: An AI-Driven Workflow for Generating Hypotheses using Large Language Models and Scientific Explanations cites this paper.
DN-Hypo-Pipeline: An AI-Driven Workflow for Generating Hypotheses using Large Language Models and Scientific Explanations ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T22:17:26.421873Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7465a901-1b6b-4988-b926-d283c48ba0f7 · inbound
DN-Hypo-Pipeline: An AI-Driven Workflow for Generating Hypotheses using Large Language Models and Scientific Explanations cites this paper.
DN-Hypo-Pipeline: An AI-Driven Workflow for Generating Hypotheses using Large Language Models and Scientific Explanations ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:09:00.647335Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7617b107-6444-487f-af8a-02423656c2e5 · inbound
Toward Generalist Autonomous Research via Hypothesis-Tree Refinement cites this paper.
Toward Generalist Autonomous Research via Hypothesis-Tree Refinement ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 79
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-03T11:28:04.228018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ff822da0-cba6-43d1-ba64-c14e416634ec · inbound
Measuring the Gap Between Human and LLM Research Ideas cites this paper.
Measuring the Gap Between Human and LLM Research Ideas ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T12:26:56.105887Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9e5c07ea-8d73-4a72-ad22-c6ba4b08073a · inbound
CausalGame: Benchmarking Causal Thinking of LLM Agents in Games cites this paper.
CausalGame: Benchmarking Causal Thinking of LLM Agents in Games ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T20:19:27.650696Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5e3cc368-8abf-45fc-92aa-83f6af3c85c2 · inbound
ResearchStudio-Idea: An Evidence-Grounded Research-Ideation Skill Suite from ML Conference Outcomes cites this paper.
ResearchStudio-Idea: An Evidence-Grounded Research-Ideation Skill Suite from ML Conference Outcomes ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:11:37.739920Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.