Paper Citation Record · LEDGER

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems

As of 20 August 2026, this Paper Citation Record lists 99 of 99 outbound references and 4 inbound Pith citation observations for arXiv:2505.17968.

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

pith.paper-citation-record.v1
2505.17968 v1

Coverage vector

measured 99 of 99 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:40:40.704557Z

measured 103 of 103 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:08:35.185016Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T00:06:37.955246Z

Reference resolution

99 of 99 outbound references displayed

verified exact0
verified fuzzy37
unresolved61
parse uncertain1
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 82402fab-ecce-4773-907f-cd8bb8afa647 · outbound

This paper cites Large-Scale Bandit Problems and KWIK Learning.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Large-Scale Bandit Problems and KWIK Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.381858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50c39405-4d30-48ca-9495-442ea9c4d0ee · outbound

This paper cites Queries and Concept Learning.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Queries and Concept Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.448282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57f7fe63-fce0-45b3-bd70-3443d251a9f7 · outbound

This paper cites Inductive Inference: Theory and Methods.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Inductive Inference: Theory and Methods

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.491594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d30d95ee-ceca-4221-a946-e5cbf8dc69cb · outbound

This paper cites Claude 3.5 sonnet.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Claude 3.5 sonnet

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.547987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9693341c-04d0-41a0-9cb9-4c3f94395333 · outbound

This paper cites Toward Efficient Exploration by Large Language Model Agents.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Toward Efficient Exploration by Large Language Model Agents

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.601633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcefdc3a-515d-4d59-93b9-9c562e09f279 · outbound

This paper cites A Markovian Decision Process.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems A Markovian Decision Process

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.640312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc58a8ce-a78f-466e-a746-4cebf820daae · outbound

This paper cites Using cognitive psychology to understand GPT-3.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Using cognitive psychology to understand GPT-3

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.682542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d291f60f-f390-4fdc-8cb9-c8ac0b12fa8c · outbound

This paper cites Variational inference: A review for statisticians.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Variational inference: A review for statisticians

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.763095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d22695ee-a3ea-41f9-8dd8-bf2b9b39962b · outbound

This paper cites R-MAX – A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems R-MAX – A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.855269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bc69ef7-5ca6-44d8-8eaf-0c4f7ce9e93c · outbound

This paper cites Language models are few-shot learners.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Language models are few-shot learners

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.911448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43339939-93b2-46e5-a19c-abb7de83b6e5 · outbound

This paper cites Why Do Multi-Agent LLM Systems Fail?.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Why Do Multi-Agent LLM Systems Fail?

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:32.993539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ce3290c-0b2a-44f6-8b06-4dd45832900d · outbound

This paper cites Bayesian Experimental Design: A Review.Statistical Science, pp.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Bayesian Experimental Design: A Review.Statistical Science, pp

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.070856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f6f2e9b-8ebe-4a0e-80b4-0d4cc2750171 · outbound

This paper cites Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.147832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51fed5c1-5bc9-4750-9138-b24393c37def · outbound

This paper cites The first crank of the cultural ratchet: Learning and transmitting concepts through language.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems The first crank of the cultural ratchet: Learning and transmitting concepts through language

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.213779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 573ec285-8443-4393-8478-1bca2ad57f2b · outbound

This paper cites CogBench: a large language model walks into a psychology lab.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems CogBench: a large language model walks into a psychology lab

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.302731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a02f0fd1-c699-42df-a7ca-9513f1fda469 · outbound

This paper cites The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.403417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c841fc75-f7d6-4854-b798-1586206b5ac9 · outbound

This paper cites Uncertainty, Information, and Sequential Experiments.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Uncertainty, Information, and Sequential Experiments

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.481437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65f83589-7dfb-43e6-8e21-a237ddcfcf42 · outbound

This paper cites PILCO: A Model-Based and Data-Efficient Approach to Policy Search.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems PILCO: A Model-Based and Data-Efficient Approach to Policy Search

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.569042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e2b302c-9af2-4c54-9c27-023bc5314e69 · outbound

This paper cites Aleatory or Epistemic? Does it Matter? Structural Safety, 31(2):105–112, 2009.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Aleatory or Epistemic? Does it Matter? Structural Safety, 31(2):105–112, 2009

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.675725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f610df2c-264d-4db8-a8fc-ce0f5c8e817a · outbound

This paper cites Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.779818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 377321d7-611e-4dd4-93f7-db14bbafc4ee · outbound

This paper cites Variational Bayesian optimal experimental design.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Variational Bayesian optimal experimental design

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.861953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a31fd6a-78f1-4d59-baae-dfc5895de5c9 · outbound

This paper cites Baby steps in evaluating the capacities of large language models.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Baby steps in evaluating the capacities of large language models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:33.954207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d67b3eaf-3302-4617-a054-1155f531c76c · outbound

This paper cites BoxingGym: Benchmarking progress in automated experimental design and model discovery.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems BoxingGym: Benchmarking progress in automated experimental design and model discovery

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.042557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a177777-7675-4fca-8622-89383c8e4bff · outbound

This paper cites Amplify scientific discovery with artificial intelligence.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Amplify scientific discovery with artificial intelligence

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.118874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2aaa365c-eb5e-49a1-963f-e3f9dac601e1 · outbound

This paper cites ANOVA: Repeated measures.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems ANOVA: Repeated measures

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.160962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b96652ac-dc3f-48b4-b0cb-b936df006f2b · outbound

This paper cites Towards an AI co-scientist.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Towards an AI co-scientist

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.213138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d509de6-b5d1-4fe6-a570-73c8714ad341 · outbound

This paper cites The Llama 3 Herd of Models.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems The Llama 3 Herd of Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.277604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e94454b9-3bf0-4669-96f1-ec0efc5c3a10 · outbound

This paper cites Bayes in the Age of Intelligent Machines.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Bayes in the Age of Intelligent Machines

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.344865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 796414a5-9386-45a3-9c79-e35aefff5510 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.407975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 997b1a60-ef79-45a8-81af-4733c6156182 · outbound

This paper cites Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.473655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1d76051-ac80-4a40-a808-7ee91b4823a7 · outbound

This paper cites GPT-4o System Card.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems GPT-4o System Card

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.532686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7974c83d-b72e-4146-a36e-208df11b3aa8 · outbound

This paper cites What Do Learning Dynamics Reveal About Generalization in LLM Reasoning?.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems What Do Learning Dynamics Reveal About Generalization in LLM Reasoning?

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.600789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81194d79-d3a4-47e4-882b-f0d6797a95f9 · outbound

This paper cites Using the tools of cognitive science to understand large language models at different levels of analysis.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Using the tools of cognitive science to understand large language models at different levels of analysis

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.640066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a170178-e8a4-4ea6-adee-ed86d9bcc9b9 · outbound

This paper cites A robust class of context- sensitive languages.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems A robust class of context- sensitive languages

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:49.565656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1d339c4b-a002-4688-9b16-c4a20db7b5e8 · outbound

This paper cites Passive learning of active causal strategies in agents and language models.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Passive learning of active causal strategies in agents and language models

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:49.352850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 08d6ff58-e230-40a8-8229-997dc742e396 · outbound

This paper cites Structured chain-of-thought prompting for code generation.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Structured chain-of-thought prompting for code generation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:49.168710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2396efc4-279d-4b28-9905-b61235b5033b · outbound

This paper cites Reducing Reinforcement Learning to KWIK Online Regression.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Reducing Reinforcement Learning to KWIK Online Regression

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:48.955565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4d7ba1ae-a463-4956-8e4a-de594c96296b · outbound

This paper cites Knows What It Knows: A Framework for Self-Aware Learning.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Knows What It Knows: A Framework for Self-Aware Learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:48.835093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 35ebf653-8272-48c8-8b50-723822d32714 · outbound

This paper cites On a measure of the information provided by an experiment.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems On a measure of the information provided by an experiment

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:34.999414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e304cd7-3ff4-4750-91d1-b9ed954c52af · outbound

This paper cites Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:48.661957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1ce2be8f-e194-42a5-87d0-115a6f41818f · outbound

This paper cites Decoupling Exploration and Exploitation for Meta-Reinforcement Learning Without Sacrifices.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Decoupling Exploration and Exploitation for Meta-Reinforcement Learning Without Sacrifices

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:48.477838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e3fe3d14-33ed-45ca-8b75-7ec14e8b2bc8 · outbound

This paper cites Large Language Models Assume People are More Rational than We Really are.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Large Language Models Assume People are More Rational than We Really are

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:35.241752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8884055-f106-44e7-a599-64123dd7f2b3 · outbound

This paper cites Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:35.314587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0913bfcd-5527-4056-921c-763140c1f2b2 · outbound

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

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:35.395340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c49abd94-62aa-43cb-8152-c385fdd9970a · outbound

This paper cites Deconstructing Long Chain-of-Thought: A Structured Reasoning Optimization Framework for Long CoT Distillation.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Deconstructing Long Chain-of-Thought: A Structured Reasoning Optimization Framework for Long CoT Distillation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:35.476624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 676edd7b-4582-4f39-86de-04ef2f90fe85 · outbound

This paper cites Category learning through active sampling.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Category learning through active sampling

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:48.302269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6c60ac6e-d798-4f3c-8d5c-a7c133cbac82 · outbound

This paper cites Is it better to select or to receive? learning via active and passive hypothesis testing.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Is it better to select or to receive? learning via active and passive hypothesis testing

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:48.147093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1841677b-fbc5-4fad-ac05-f55ef2ea0065 · outbound

This paper cites Modeling rapid language learning by distilling Bayesian priors into artificial neural networks.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Modeling rapid language learning by distilling Bayesian priors into artificial neural networks

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:35.712060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05f80f70-7c1a-4c6d-a7a7-c357f7027ba9 · outbound

This paper cites Embers of autoregression show how large language models are shaped by the problem they are trained to solve.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Embers of autoregression show how large language models are shaped by the problem they are trained to solve

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:47.995708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e3be7c28-fb95-48a7-a078-4fd94a17d26a · outbound

This paper cites MatPilot: an LLM-enabled AI Materials Scientist under the Framework of Human-Machine Collaboration.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems MatPilot: an LLM-enabled AI Materials Scientist under the Framework of Human-Machine Collaboration

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:35.888952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caa38cd3-48dd-4eef-81c8-b9f9bf08921f · outbound

This paper cites Sparks of Science: Hypothesis Generation Using Structured Paper Data.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Sparks of Science: Hypothesis Generation Using Structured Paper Data

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:36.009484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c36647d-194f-4806-981d-f738f5196c12 · outbound

This paper cites (More) Efficient Reinforcement Learning via Posterior Sampling.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems (More) Efficient Reinforcement Learning via Posterior Sampling

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:47.815242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 038b21dc-64a8-4b1e-978d-80f4a4284dc1 · outbound

This paper cites Puterman.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Puterman

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:47.645625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 844a8a34-8b35-471e-8b6e-faea4f154c0c · outbound

This paper cites Towards scientific discovery with generative ai: Progress, opportunities, and challenges.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Towards scientific discovery with generative ai: Progress, opportunities, and challenges

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:47.543996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 61eec6b9-b181-4567-a92f-b729e4834598 · outbound

This paper cites Diversity-Based Inference of Finite Automata.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Diversity-Based Inference of Finite Automata

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:47.335383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e096bed7-de24-4dad-a5fe-528ebfa59b43 · outbound

This paper cites Inference of Finite Automata Using Homing Sequences.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Inference of Finite Automata Using Homing Sequences

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:47.116883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 391f4971-cca2-42ce-b42e-b7e909f1f4f5 · outbound

This paper cites Jagadish, Marvin Mathony, Tobias Ludwig, and Eric Schulz.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Jagadish, Marvin Mathony, Tobias Ludwig, and Eric Schulz

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:36.544531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac32d513-3360-4f9d-a0a6-e992cb0f6269 · outbound

This paper cites Symbolic metaprogram search improves learning efficiency and explains rule learning in humans.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Symbolic metaprogram search improves learning efficiency and explains rule learning in humans

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:46.746513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b397f9fd-5cb7-4c33-a49c-73948ca38d19 · outbound

This paper cites Trading off Mistakes and Don’t- Know Predictions.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Trading off Mistakes and Don’t- Know Predictions

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:46.416593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c0a039d9-d524-4528-b9c8-acf3dc5d5e92 · outbound

This paper cites Agent Laboratory: Using LLM Agents as Research Assistants.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Agent Laboratory: Using LLM Agents as Research Assistants

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:36.829520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c74deb9-8ff3-4bd5-8068-21cb2a079a07 · outbound

This paper cites Active Learning Literature Survey.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Active Learning Literature Survey

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:46.070277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 439cc0a6-169c-4dfb-a18c-432cc02b15ec · outbound

This paper cites Llm-sr: Scientific equation discovery via programming with large language models.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Llm-sr: Scientific equation discovery via programming with large language models

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:45.807125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 28738de6-bb3c-4bfb-8ab9-454ce709f0e5 · outbound

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

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:37.118461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7290d399-1b29-42ab-bc4f-f3030c56f46e · outbound

This paper cites To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:37.243258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 971622c1-4ba9-46c2-ab12-73b9b13d43ba · outbound

This paper cites PaperBench: Evaluating AI's Ability to Replicate AI Research.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems PaperBench: Evaluating AI's Ability to Replicate AI Research

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:37.301272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae21c6d6-7306-4574-a60b-247ea474c416 · outbound

This paper cites An Analysis of Model-based interval estimation for Markov Decision Processes.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems An Analysis of Model-based interval estimation for Markov Decision Processes

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:45.551239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 35f9fa0f-d275-4436-88e0-646ebed51a86 · outbound

This paper cites A Bayesian framework for reinforcement learning.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems A Bayesian framework for reinforcement learning

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:45.290247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 87f047f3-9fbf-4cf9-b538-640ffa5b6c2a · outbound

This paper cites Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:37.537997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c3ffde1-9c2f-435d-84b1-6a78dc4c7403 · outbound

This paper cites Integrated architectures for learning, planning, and reacting based on approximating dynamic programming.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Integrated architectures for learning, planning, and reacting based on approximating dynamic programming

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:45.084955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e35a777f-eb96-4192-b9e3-aacbbb0f762c · outbound

This paper cites Dyna, an integrated architecture for learning, planning, and reacting.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Dyna, an integrated architecture for learning, planning, and reacting

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:37.794791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58d2fbfd-c0df-4dcc-94c2-ab0efdb77019 · outbound

This paper cites Introduction to Reinforcement Learning.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Introduction to Reinforcement Learning

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:44.912222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 028339c6-93e4-4e83-8fe3-50410e086460 · outbound

This paper cites Agnostic KWIK learning and Efficient Approximate Reinforcement Learning.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Agnostic KWIK learning and Efficient Approximate Reinforcement Learning

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:44.696029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9f2ec0af-3f1c-48dd-9e1d-f7c7ec585536 · outbound

This paper cites Active exploration in dynamic environments.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Active exploration in dynamic environments

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:44.516965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3af49d99-a977-495d-b799-48b19f383d99 · outbound

This paper cites Exploring Compact Reinforcement-Learning Representations with Linear Regression.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Exploring Compact Reinforcement-Learning Representations with Linear Regression

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:44.353743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 777acb38-9e0d-463b-9206-3e95660ebe3c · outbound

This paper cites Scientific Discovery in the Age of Artificial Intelligence.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Scientific Discovery in the Age of Artificial Intelligence

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:44.215739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b6f8b0d4-7ab8-4cd1-8299-3f881701ac04 · outbound

This paper cites Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:38.414916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92d3dbcd-db87-46df-84ab-0cd4783b1d68 · outbound

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

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Chain-of-thought prompting elicits reasoning in large language models

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:38.504795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eabe149f-13cf-467b-9b42-111b84afa1ed · outbound

This paper cites An explanation of in-context learning as implicit Bayesian inference.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems An explanation of in-context learning as implicit Bayesian inference

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:44.071384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ba0347c7-6571-4e20-9d66-1b705672e0b1 · outbound

This paper cites Piantadosi.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Piantadosi

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:43.980017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c6fa9a29-8b5d-4f61-90c6-ee414cc17cf0 · outbound

This paper cites On Benchmarking Human-Like Intelligence in Machines.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems On Benchmarking Human-Like Intelligence in Machines

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:38.848439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d8b21e7-8c45-47e4-8a79-bc16e3fb95a8 · outbound

This paper cites People use fast, goal-directed simulation to reason about novel games.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems People use fast, goal-directed simulation to reason about novel games

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:38.988889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d74f7bd-c2f4-43c7-943a-c49c357804a9 · outbound

This paper cites Eliciting the Priors of Large Language Models using Iterated In-Context Learning.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Eliciting the Priors of Large Language Models using Iterated In-Context Learning

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:39.080062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd18fa2d-5a8c-4ce0-b329-e413ad30db57 · outbound

This paper cites Incoherent Probability Judgments in Large Language Models.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Incoherent Probability Judgments in Large Language Models

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:39.192857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdf9af22-6755-463d-9fae-66dd7bb25d63 · outbound

This paper cites Provide a thorough reasoning before performing the action.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Provide a *thorough reasoning* before performing the action

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:43.903505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1b26e766-d0ee-4bc4-9852-8428de509d9a · outbound

This paper cites [5 point].

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems [5 point]

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:43.769540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 402086e6-04fc-44ae-b9b7-d37854a3b984 · outbound

This paper cites You will then output a score based on a set of assessment criteria.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems You will then output a score based on a set of assessment criteria

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:43.565586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2bd083ca-20b8-4d2e-ab63-70b2b9c2bba2 · outbound

This paper cites [3 points].

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems [3 points]

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:43.409550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 02f91f73-9274-43e4-bdab-e63008affb85 · outbound

This paper cites an unresolved cited work.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:40:43.238105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e0ab5211-cae1-4849-b8df-a67c01c50722 · outbound

This paper cites an unresolved cited work.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:40:43.073924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f8de0d1e-0dd6-4bfa-82fc-2dc4efb0b8c7 · outbound

This paper cites (Note that there will be multiple a_i 's.).

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems (Note that there will be multiple a_i 's.)

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:42.903921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7dde8e8c-00b8-4453-9b44-b0a605a0a75b · outbound

This paper cites an unresolved cited work.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Unresolved cited work

Reference 91

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:40:42.815299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 091783d3-1335-4dc9-b82b-376aa5d26901 · outbound

This paper cites an unresolved cited work.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Unresolved cited work

Reference 92

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:40:42.686738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1e0f90f9-c980-41b2-b8ff-5de72fd2854d · outbound

This paper cites The score for this bullet should be the accuracy percentage times the total allocated 6 points [6 points].

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems The score for this bullet should be the accuracy percentage times the total allocated 6 points [6 points]

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:42.535878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5c06d16d-e10c-4406-b32f-7e9fbd3d8dd9 · outbound

This paper cites an unresolved cited work.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Unresolved cited work

Reference 94

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:40:42.440082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1161a586-9ef7-4cc8-9640-82a58d2a0058 · outbound

This paper cites Win by connecting 3 stones in a column.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Win by connecting 3 stones in a column

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:42.304484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a46dffa2-aae7-4f09-8573-a72c4beaa0a2 · outbound

This paper cites an unresolved cited work.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Unresolved cited work

Reference 96

Resolution: parse uncertain; raw_fallback, observed 2026-08-07T14:40:42.165301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation aa59d39a-2c8a-4d6f-8c50-875550e5f662 · outbound

This paper cites an unresolved cited work.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Unresolved cited work

Reference 97

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:40:41.981797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 93d5b542-c867-4482-b680-55190bd4d052 · outbound

This paper cites an unresolved cited work.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems Unresolved cited work

Reference 98

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:40:41.848711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 99ce0b0d-b0af-4510-9b0a-d475301ec7dc · outbound

This paper cites AAA", "BBB.

Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems AAA", "BBB

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:40:41.698993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 3a5a7a26-a078-46cd-b7f9-9315ee619eec · 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 Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems

Reference 293

Resolution: verified exact; arxiv_id, observed 2026-05-14T22:23:15.430452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f0ecc73d-9b18-4cec-9108-f6ee09342aa6 · inbound

CausalGame: Benchmarking Causal Thinking of LLM Agents in Games cites this paper.

CausalGame: Benchmarking Causal Thinking of LLM Agents in Games Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems

Reference 3

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 5bddc95b-cf75-4d8b-bd2c-3374077b922a · inbound

Mining Workflow Graphs for Black-Box Boundary Testing of Conversational LLM Agents cites this paper.

Mining Workflow Graphs for Black-Box Boundary Testing of Conversational LLM Agents Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems

Reference 26

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T00:06:37.956842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a46cf61d-ded2-48af-ba09-31842ab7a8c3 · inbound

DiG-bench: Discovery in Games cites this paper.

DiG-bench: Discovery in Games Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T00:08:35.185016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.