Paper Citation Record · LEDGER

Predicting Empirical AI Research Outcomes with Language Models

As of 8 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 3 inbound Pith citation observations for arXiv:2506.00794.

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

pith.paper-citation-record.v1
2506.00794 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:05:56.920833Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:46:32.625500Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

19 of 19 outbound references displayed

verified exact0
verified fuzzy4
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation eeedf0a2-6028-41b2-88b6-a18fc3c612c4 · outbound

This paper cites Humans vs Large Language Models: Judgmental Forecasting in an Era of Advanced AI.

Predicting Empirical AI Research Outcomes with Language Models Humans vs Large Language Models: Judgmental Forecasting in an Era of Advanced AI

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:55.463704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5afbfc62-d585-46c0-b450-f74f715fbc02 · outbound

This paper cites LitLLM: A Toolkit for Scientific Literature Review.

Predicting Empirical AI Research Outcomes with Language Models LitLLM: A Toolkit for Scientific Literature Review

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:55.548904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc8f2d72-b221-469b-ae01-f7db11fb3458 · outbound

This paper cites Alpacafarm: A simulation framework for methods that learn from human feedback.

Predicting Empirical AI Research Outcomes with Language Models Alpacafarm: A simulation framework for methods that learn from human feedback

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:55.630510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1aa981e8-d446-4ee9-b2e8-61bed3beb569 · outbound

This paper cites Towards an AI co-scientist.

Predicting Empirical AI Research Outcomes with Language Models Towards an AI co-scientist

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:55.709041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49b6c088-00af-4006-bb02-7765bf1c0c7a · outbound

This paper cites Approaching Human-Level Forecasting with Language Models.

Predicting Empirical AI Research Outcomes with Language Models Approaching Human-Level Forecasting with Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:55.787770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdc97199-e562-4ef9-abd7-04dff8b60230 · outbound

This paper cites MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation.

Predicting Empirical AI Research Outcomes with Language Models MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:55.906410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cd05966-ff5e-464d-9e8a-51b3cec2e9f0 · outbound

This paper cites ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities.

Predicting Empirical AI Research Outcomes with Language Models ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:55.960132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4296a1ca-9f15-4fae-a8ed-b57e1d4e8ce4 · outbound

This paper cites Can large language models provide useful feedback on research papers? a large-scale empirical analysis.

Predicting Empirical AI Research Outcomes with Language Models Can large language models provide useful feedback on research papers? a large-scale empirical analysis

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:57.932804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2c1e4a31-56d0-4603-a789-7efdf5865715 · outbound

This paper cites The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery.

Predicting Empirical AI Research Outcomes with Language Models The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:56.133782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38538177-e28b-497e-a42a-d26786893a42 · outbound

This paper cites Large language models surpass human experts in predicting neuroscience results.

Predicting Empirical AI Research Outcomes with Language Models Large language models surpass human experts in predicting neuroscience results

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:57.711264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ffb9baa2-5f72-488d-a125-056f2bf2e482 · outbound

This paper cites Neurips 2021 summary, 2021.

Predicting Empirical AI Research Outcomes with Language Models Neurips 2021 summary, 2021

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:57.544494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0dde4865-f67f-48c4-b329-bb5f47e9ba75 · outbound

This paper cites Automatic Prompt Optimization with "Gradient Descent" and Beam Search.

Predicting Empirical AI Research Outcomes with Language Models Automatic Prompt Optimization with "Gradient Descent" and Beam Search

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:56.352320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb511723-d2e8-495a-bfb2-835ceb4dc392 · outbound

This paper cites Large Language Model Prediction Capabilities: Evidence from a Real-World Forecasting Tournament.

Predicting Empirical AI Research Outcomes with Language Models Large Language Model Prediction Capabilities: Evidence from a Real-World Forecasting Tournament

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:56.438248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4095f34d-131c-4688-80e5-493e69d74eb7 · outbound

This paper cites Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers.

Predicting Empirical AI Research Outcomes with Language Models Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:56.506033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45f0081e-14e6-41e4-a1a7-3671dc72148b · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Predicting Empirical AI Research Outcomes with Language Models Chain-of-thought prompting elicits reasoning in large language models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:56.611944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ad5eaaa-d310-4f25-8756-19b310dafb9b · outbound

This paper cites The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search.

Predicting Empirical AI Research Outcomes with Language Models The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:56.687259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcad7cf2-68d6-4dcf-9079-bf410cf2d921 · outbound

This paper cites Star: Self-taught reasoner bootstrapping reasoning with reasoning.

Predicting Empirical AI Research Outcomes with Language Models Star: Self-taught reasoner bootstrapping reasoning with reasoning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:56.756008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25018129-528f-42b4-a652-008c26bb6588 · outbound

This paper cites Goal driven discovery of distributional differences via language descriptions.

Predicting Empirical AI Research Outcomes with Language Models Goal driven discovery of distributional differences via language descriptions

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:05:57.331730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8a627cc6-e1e6-4218-9782-d04bf14298e5 · outbound

This paper cites Forecasting Future World Events with Neural Networks.

Predicting Empirical AI Research Outcomes with Language Models Forecasting Future World Events with Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:56.920833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 75729d29-f9d4-45d6-9258-680d865673ea · inbound

The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas cites this paper.

The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas Predicting Empirical AI Research Outcomes with Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T22:46:32.625500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad6885f1-249d-4223-b8d8-ee4b259d3fc8 · inbound

Advancing Event Forecasting through Massive Training of Large Language Models: Challenges, Solutions, and Broader Impacts cites this paper.

Advancing Event Forecasting through Massive Training of Large Language Models: Challenges, Solutions, and Broader Impacts Predicting Empirical AI Research Outcomes with Language Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T14:22:31.403988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f01eadf-26ff-4fc2-a488-672666bbc266 · inbound

When AI reviews science: Can we trust the referee? cites this paper.

When AI reviews science: Can we trust the referee? Predicting Empirical AI Research Outcomes with Language Models

Reference 102

Resolution: verified exact; arxiv_id, observed 2026-05-08T23:19:30.523123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.