Paper Citation Record · LEDGER

Aviary: training language agents on challenging scientific tasks

As of 12 August 2026, this Paper Citation Record lists 100 of 141 outbound references and 14 inbound Pith citation observations for arXiv:2412.21154.

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

pith.paper-citation-record.v1
2412.21154 v1

Coverage vector

measured 100 of 141 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:07:33.867159Z

measured 114 of 114 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:06:30.848762Z

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

100 of 141 outbound references displayed

verified exact3
verified fuzzy0
unresolved97
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

7
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 6180c91c-2424-4759-ba91-5a13175b8989 · outbound

This paper cites Augmented language models: a survey.

Aviary: training language agents on challenging scientific tasks Augmented language models: a survey

Reference 1

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Observation 2538c30d-078d-4cc2-841b-b172a3ebed34 · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Aviary: training language agents on challenging scientific tasks The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.392173Z

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Observation d64cffc2-f9aa-4f1c-bd28-8ee82fdebb77 · outbound

This paper cites Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives.

Aviary: training language agents on challenging scientific tasks Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives

Reference 3

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Observation 9d02a97b-35df-4e0a-b123-56f203da1a69 · outbound

This paper cites Cognitive architectures for language agents.

Aviary: training language agents on challenging scientific tasks Cognitive architectures for language agents

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.402162Z

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Observation fb34f7ff-ce4c-449a-96ca-ed58e5a852e7 · outbound

This paper cites Artificial intelligence: a modern approach.

Aviary: training language agents on challenging scientific tasks Artificial intelligence: a modern approach

Reference 5

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Observation 5065718a-2a76-4cf3-829e-f6181c6effd1 · outbound

This paper cites Language models are few-shot learners.

Aviary: training language agents on challenging scientific tasks Language models are few-shot learners

Reference 6

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Observation af629ff8-185c-4cfd-8daf-f013369a156d · outbound

This paper cites GPT-4 Technical Report.

Aviary: training language agents on challenging scientific tasks GPT-4 Technical Report

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.417794Z

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Observation 68a857ae-0d17-4be2-afd7-006318628d2a · outbound

This paper cites Eight Things to Know about Large Language Models.

Aviary: training language agents on challenging scientific tasks Eight Things to Know about Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.425629Z

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Observation 43850ee3-667f-41ec-9324-0c5bfb7b48eb · outbound

This paper cites Socratic models: Composing zero-shot multimodal reasoning with language.

Aviary: training language agents on challenging scientific tasks Socratic models: Composing zero-shot multimodal reasoning with language

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.430726Z

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Observation ff93b275-7fb5-4b32-99aa-eadc1c64e584 · outbound

This paper cites Large language models as generalizable policies for embodied tasks.

Aviary: training language agents on challenging scientific tasks Large language models as generalizable policies for embodied tasks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.436138Z

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Observation d3f31d49-cc9f-4cdc-a4df-3446facaa75e · outbound

This paper cites Building machines that learn and think like people.

Aviary: training language agents on challenging scientific tasks Building machines that learn and think like people

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.441582Z

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Observation 02f71549-a026-45a9-bf66-83c0ce5bea34 · outbound

This paper cites Selection-inference: exploiting large language models for interpretable logical reasoning.

Aviary: training language agents on challenging scientific tasks Selection-inference: exploiting large language models for interpretable logical reasoning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.448853Z

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Observation 41b21e00-36d0-4199-ac90-223bc2525014 · outbound

This paper cites Mathematical capabilities of ChatGPT.

Aviary: training language agents on challenging scientific tasks Mathematical capabilities of ChatGPT

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.454669Z

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Observation 58ace688-4d0c-44ac-8586-f05b05bb7fd0 · outbound

This paper cites Data for mathematical copilots: Better ways of presenting proofs for machine learning.

Aviary: training language agents on challenging scientific tasks Data for mathematical copilots: Better ways of presenting proofs for machine learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.460363Z

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Observation d3e22c8a-cbbb-4d67-8373-885f0174f84c · outbound

This paper cites Do as I can, not as I say: grounding language in robotic affordances.

Aviary: training language agents on challenging scientific tasks Do as I can, not as I say: grounding language in robotic affordances

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.465235Z

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Observation 481f81d3-82a9-4d1d-a7f4-d37e19f49de2 · outbound

This paper cites Language models as zero-shot planners: Extracting actionable knowledge for embodied agents.

Aviary: training language agents on challenging scientific tasks Language models as zero-shot planners: Extracting actionable knowledge for embodied agents

Reference 16

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Observation 1ea59a32-e039-4b51-8940-66732716053a · outbound

This paper cites Collaborating with language models for embodied reasoning.

Aviary: training language agents on challenging scientific tasks Collaborating with language models for embodied reasoning

Reference 17

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Observation 93aa2964-35cb-4da1-9441-9c37b305b4e0 · outbound

This paper cites ReAct: synergizing reasoning and acting in language models.

Aviary: training language agents on challenging scientific tasks ReAct: synergizing reasoning and acting in language models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.482216Z

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Observation aafd3832-7592-4df2-b52b-d6c68aec1e09 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

Aviary: training language agents on challenging scientific tasks Reflexion: Language agents with verbal reinforcement learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.487165Z

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Observation 16813500-e8f3-4357-848d-7abe1869c62c · outbound

This paper cites Reasoning with language model is planning with world model.

Aviary: training language agents on challenging scientific tasks Reasoning with language model is planning with world model

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.491973Z

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Observation 82cc0d2c-a890-4863-ab0d-d0089d6aa135 · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.

Aviary: training language agents on challenging scientific tasks Tree of thoughts: Deliberate problem solving with large language models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.496248Z

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Observation 70a69064-1479-4e95-b0d2-fe4055c8e365 · outbound

This paper cites Generative agents: Interactive simulacra of human behavior.

Aviary: training language agents on challenging scientific tasks Generative agents: Interactive simulacra of human behavior

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.500877Z

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Observation 7ed892a5-c525-4ec2-9f09-8e7f811602f3 · outbound

This paper cites V oyager: An open-ended embodied agent with large language models.Transactions on Machine Learning Research, 2024.

Aviary: training language agents on challenging scientific tasks V oyager: An open-ended embodied agent with large language models.Transactions on Machine Learning Research, 2024

Reference 23

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Observation 47fb4dae-35cc-4994-9b24-ee5006330652 · outbound

This paper cites GPTSwarm: Language agents as optimizable graphs.

Aviary: training language agents on challenging scientific tasks GPTSwarm: Language agents as optimizable graphs

Reference 24

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Observation 1f1e4110-71bf-4adc-921a-c2f2cc1e2ff2 · outbound

This paper cites TextGrad: Automatic "Differentiation" via Text.

Aviary: training language agents on challenging scientific tasks TextGrad: Automatic "Differentiation" via Text

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.513751Z

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Observation bdb87e88-420e-4934-ac49-0bbb4b3d1c09 · outbound

This paper cites Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs.

Aviary: training language agents on challenging scientific tasks Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Reference 26

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Observation 7717f671-134e-4e2c-a79d-d97cd35f22a5 · outbound

This paper cites Gradient estimation using stochastic computation graphs.

Aviary: training language agents on challenging scientific tasks Gradient estimation using stochastic computation graphs

Reference 27

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Observation 080f4cb8-9cfe-4f1c-8b1b-ed4e875750d0 · outbound

This paper cites Thinking fast and slow with deep learning and tree search.

Aviary: training language agents on challenging scientific tasks Thinking fast and slow with deep learning and tree search

Reference 28

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Observation 038527bd-1b54-4e08-b5a4-3f18b73f2653 · outbound

This paper cites Expert iteration.

Aviary: training language agents on challenging scientific tasks Expert iteration

Reference 29

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Observation f8af6422-b7ed-4ed2-9ca0-443a8db8c5e7 · outbound

This paper cites Teaching Large Language Models to Reason with Reinforcement Learning.

Aviary: training language agents on challenging scientific tasks Teaching Large Language Models to Reason with Reinforcement Learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.546798Z

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Observation 82f1d022-a663-47c7-921c-a59420bdc7f2 · outbound

This paper cites Solving math word problems with process- and outcome-based feedback.

Aviary: training language agents on challenging scientific tasks Solving math word problems with process- and outcome-based feedback

Reference 31

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Observation 960ffab6-26f9-4a60-b6b2-36019c156ad0 · outbound

This paper cites Let’s verify step by step.

Aviary: training language agents on challenging scientific tasks Let’s verify step by step

Reference 32

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Observation 21e3d268-e0c0-4f85-a1a8-71d965faf82c · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Aviary: training language agents on challenging scientific tasks Training Verifiers to Solve Math Word Problems

Reference 33

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Observation 65bad622-9ba3-4b1a-af02-00bad5ee64d6 · outbound

This paper cites HotpotQA: A dataset for diverse, explainable multi-hop question answering.

Aviary: training language agents on challenging scientific tasks HotpotQA: A dataset for diverse, explainable multi-hop question answering

Reference 34

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Observation 64e798b4-fb1c-4b51-bd1c-4c024246239d · outbound

This paper cites LAB-Bench: Measuring Capabilities of Language Models for Biology Research.

Aviary: training language agents on challenging scientific tasks LAB-Bench: Measuring Capabilities of Language Models for Biology Research

Reference 35

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Observation a6302a04-7e35-4184-ac23-0c5bc906c2b4 · outbound

This paper cites PaperQA: Retrieval-Augmented Generative Agent for Scientific Research.

Aviary: training language agents on challenging scientific tasks PaperQA: Retrieval-Augmented Generative Agent for Scientific Research

Reference 36

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Observation 1842e80a-1032-4345-805d-b8c4cb794db8 · outbound

This paper cites Language agents achieve superhuman synthesis of scientific knowledge.

Aviary: training language agents on challenging scientific tasks Language agents achieve superhuman synthesis of scientific knowledge

Reference 37

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Aviary: training language agents on challenging scientific tasks Unresolved cited work

Reference 38

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Observation ea04faf5-3bb2-4a28-9ac8-5681a81b0b93 · outbound

This paper cites A new age in protein design empowered by deep learning.

Aviary: training language agents on challenging scientific tasks A new age in protein design empowered by deep learning

Reference 39

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Observation 90eba777-afeb-46e9-a136-f7ab22d18773 · outbound

This paper cites CRISPR-GPT for Agentic Automation of Gene-editing Experiments.

Aviary: training language agents on challenging scientific tasks CRISPR-GPT for Agentic Automation of Gene-editing Experiments

Reference 40

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Observation c6c991a1-2a68-4562-8a80-c8839bbe1c41 · outbound

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Aviary: training language agents on challenging scientific tasks LLM-powered autonomous agents

Reference 41

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This paper cites Grounding large language models in interactive environments with online reinforcement learning.

Aviary: training language agents on challenging scientific tasks Grounding large language models in interactive environments with online reinforcement learning

Reference 42

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Observation 940a46b7-3fc8-4298-b54d-ef8dfbc32b69 · outbound

This paper cites Pangu-Agent: A Fine-Tunable Generalist Agent with Structured Reasoning.

Aviary: training language agents on challenging scientific tasks Pangu-Agent: A Fine-Tunable Generalist Agent with Structured Reasoning

Reference 43

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This paper cites Reinforcing Language Agents via Policy Optimization with Action Decomposition.

Aviary: training language agents on challenging scientific tasks Reinforcing Language Agents via Policy Optimization with Action Decomposition

Reference 44

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This paper cites Entropy-Regularized Token-Level Policy Optimization for Language Agent Reinforcement.

Aviary: training language agents on challenging scientific tasks Entropy-Regularized Token-Level Policy Optimization for Language Agent Reinforcement

Reference 45

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This paper cites DynaSaur: Large Language Agents Beyond Predefined Actions.

Aviary: training language agents on challenging scientific tasks DynaSaur: Large Language Agents Beyond Predefined Actions

Reference 46

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Observation ac43e7f8-0af6-441c-a216-30d54a835a2d · outbound

This paper cites Enhancing Decision-Making for LLM Agents via Step-Level Q-Value Models.

Aviary: training language agents on challenging scientific tasks Enhancing Decision-Making for LLM Agents via Step-Level Q-Value Models

Reference 47

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This paper cites Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents.

Aviary: training language agents on challenging scientific tasks Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents

Reference 48

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Observation 2a902eda-4027-42fc-bff4-97340124857a · outbound

This paper cites On the Design and Analysis of LLM-Based Algorithms.

Aviary: training language agents on challenging scientific tasks On the Design and Analysis of LLM-Based Algorithms

Reference 49

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Aviary: training language agents on challenging scientific tasks LangChain, October 2022

Reference 50

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Aviary: training language agents on challenging scientific tasks LlamaIndex, November 2022

Reference 51

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Observation 1453a5ce-39b9-444f-8e99-27eca6d3611e · outbound

This paper cites Cost-effective hyperparameter optimization for large language model generation inference.

Aviary: training language agents on challenging scientific tasks Cost-effective hyperparameter optimization for large language model generation inference

Reference 52

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Observation 8dd93e97-28c8-4722-996b-82cc9e99d2c7 · outbound

This paper cites AutoPrompt: Eliciting knowledge from language models with automatically generated prompts.

Aviary: training language agents on challenging scientific tasks AutoPrompt: Eliciting knowledge from language models with automatically generated prompts

Reference 53

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Observation e9fc9be2-b970-416e-8476-93674eae9568 · outbound

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Aviary: training language agents on challenging scientific tasks Prefix-tuning: Optimizing continuous prompts for generation

Reference 54

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Aviary: training language agents on challenging scientific tasks Visual prompt tuning

Reference 55

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Observation c31ab3ba-cf77-4a34-9dc4-66377fca2c26 · outbound

This paper cites Knowprompt: Knowledge-aware prompt-tuning with synergistic optimization for relation extraction.

Aviary: training language agents on challenging scientific tasks Knowprompt: Knowledge-aware prompt-tuning with synergistic optimization for relation extraction

Reference 56

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Observation 820fd18c-8a5e-4a71-96a5-8c964f92567f · outbound

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Aviary: training language agents on challenging scientific tasks Learning how to ask: Querying lms with mixtures of soft prompts

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.679704Z

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Observation d513f980-4203-42f0-9bdd-cd0c4d312fbd · outbound

This paper cites Connecting large language models with evolutionary algorithms yields powerful prompt optimizers.

Aviary: training language agents on challenging scientific tasks Connecting large language models with evolutionary algorithms yields powerful prompt optimizers

Reference 58

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Observation 7fafde82-20a6-4bc5-b804-98121dec0f58 · outbound

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Aviary: training language agents on challenging scientific tasks Are Large Language Models Good Prompt Optimizers?

Reference 59

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Observation c8281ca2-1104-4ad9-af81-3a5bb0d7f04b · outbound

This paper cites Revisiting OPRO: The Limitations of Small-Scale LLMs as Optimizers.

Aviary: training language agents on challenging scientific tasks Revisiting OPRO: The Limitations of Small-Scale LLMs as Optimizers

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.691882Z

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Observation 650f8fdf-cdbc-49ea-bc26-e6feb6ce60ec · outbound

This paper cites Black-Box Prompt Optimization: Aligning Large Language Models without Model Training.

Aviary: training language agents on challenging scientific tasks Black-Box Prompt Optimization: Aligning Large Language Models without Model Training

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.696382Z

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Observation 7ffe4ee7-1d0e-4f04-aa3e-d19139fc62db · outbound

This paper cites Large language models as optimizers.

Aviary: training language agents on challenging scientific tasks Large language models as optimizers

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.700536Z

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Observation ec9f4328-e261-4be2-a909-0ec335e33e09 · outbound

This paper cites Prompt Optimization with Human Feedback.

Aviary: training language agents on challenging scientific tasks Prompt Optimization with Human Feedback

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.704436Z

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Observation 9217b97a-7026-45e1-9f28-b71ca27f9c18 · outbound

This paper cites Localized Zeroth-Order Prompt Optimization.

Aviary: training language agents on challenging scientific tasks Localized Zeroth-Order Prompt Optimization

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Resolution: verified exact; local_arxiv, observed 2026-08-10T23:07:34.718017Z

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Observation 363baabc-7b1c-4356-ae07-83640c8c7396 · outbound

This paper cites Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars.

Aviary: training language agents on challenging scientific tasks Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars

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Resolution: verified exact; local_arxiv, observed 2026-08-10T23:07:34.696904Z

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Observation bc3ee02a-4325-4c1f-90cb-ee88a7a7a5c3 · outbound

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Aviary: training language agents on challenging scientific tasks Use your INSTINCT: INSTruction optimization for LLMs using neural bandits coupled with transformers

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.717950Z

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Observation 8caf4110-7820-4cbe-b771-f33213ea1b0a · outbound

This paper cites InstructZero: Efficient instruction optimization for black-box large language models.

Aviary: training language agents on challenging scientific tasks InstructZero: Efficient instruction optimization for black-box large language models

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.722190Z

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Observation 25bf8b9f-26fb-4dac-9148-4c6f23d3fb45 · outbound

This paper cites Large language models are human-level prompt engineers.

Aviary: training language agents on challenging scientific tasks Large language models are human-level prompt engineers

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.727099Z

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Observation ea648be5-0025-4f90-8405-c014a24c4a83 · outbound

This paper cites Automatic prompt optimization with ”gradient descent” and beam search.

Aviary: training language agents on challenging scientific tasks Automatic prompt optimization with ”gradient descent” and beam search

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.731426Z

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Observation 0acaf731-805f-49c5-bd84-fd0e487dfa4f · outbound

This paper cites Prompt optimization in large language models.

Aviary: training language agents on challenging scientific tasks Prompt optimization in large language models

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.735422Z

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Observation 0f4d7dce-ef24-4b6f-8cb1-d32d10648e98 · outbound

This paper cites MAPO: Boosting large language model performance with model-adaptive prompt optimization.

Aviary: training language agents on challenging scientific tasks MAPO: Boosting large language model performance with model-adaptive prompt optimization

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.739636Z

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Observation 7891aed2-b308-4a3a-9ba2-77bbf5cd1c38 · outbound

This paper cites PromptAgent: Strategic planning with language models enables expert-level prompt optimization.

Aviary: training language agents on challenging scientific tasks PromptAgent: Strategic planning with language models enables expert-level prompt optimization

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.743782Z

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Observation 8e66e460-9d52-4a97-a98f-a59f4076fc86 · outbound

This paper cites Improving Text-to-Image Consistency via Automatic Prompt Optimization.

Aviary: training language agents on challenging scientific tasks Improving Text-to-Image Consistency via Automatic Prompt Optimization

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.747704Z

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Observation ae4682a9-8ecb-41f4-9e9a-cbafce9f93cd · outbound

This paper cites Prompt Optimization via Adversarial In-Context Learning.

Aviary: training language agents on challenging scientific tasks Prompt Optimization via Adversarial In-Context Learning

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Resolution: verified exact; local_arxiv, observed 2026-08-10T23:07:34.659149Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c76a1774-f5e0-4990-98f6-db6e40ccfb0f · outbound

This paper cites Joint prompt optimization of stacked LLMs using variational inference.

Aviary: training language agents on challenging scientific tasks Joint prompt optimization of stacked LLMs using variational inference

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.756044Z

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Observation c3b771ab-7c36-41ff-a56a-6f9caeb8be5f · outbound

This paper cites A Bayesian approach for prompt optimization in pre-trained language models.

Aviary: training language agents on challenging scientific tasks A Bayesian approach for prompt optimization in pre-trained language models

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.759905Z

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Observation 72452f49-29f5-4b99-b3b8-522bce347980 · outbound

This paper cites Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery.

Aviary: training language agents on challenging scientific tasks Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.764222Z

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Observation ac1b34fa-fee3-4217-8af0-4087e76eeaaf · outbound

This paper cites Prompt Engineering a Prompt Engineer.

Aviary: training language agents on challenging scientific tasks Prompt Engineering a Prompt Engineer

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.768523Z

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Observation 0c4a27d8-b12f-4c2d-a10f-c921ac559b00 · outbound

This paper cites AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning.

Aviary: training language agents on challenging scientific tasks AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.772508Z

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Observation 2d2048da-d857-4899-9dbe-4945caa4fb8c · outbound

This paper cites Tool Learning with Large Language Models: A Survey.

Aviary: training language agents on challenging scientific tasks Tool Learning with Large Language Models: A Survey

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.776780Z

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Observation 4c1220eb-5167-4fe2-b27e-8e5ac178af54 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

Aviary: training language agents on challenging scientific tasks Toolformer: Language models can teach themselves to use tools

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.781147Z

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Observation 72a9ccd7-6390-4459-a8d1-0a977c427e82 · outbound

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Aviary: training language agents on challenging scientific tasks Tool Learning with Foundation Models

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.785252Z

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Observation e5813349-3da8-433a-a296-8f5be836d12f · outbound

This paper cites Agent Lumos: Unified and modular training for open-source language agents.

Aviary: training language agents on challenging scientific tasks Agent Lumos: Unified and modular training for open-source language agents

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.789778Z

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Observation ba44ec4d-2b4a-47dd-8aaa-2240df239c63 · outbound

This paper cites Symbolic Learning Enables Self-Evolving Agents.

Aviary: training language agents on challenging scientific tasks Symbolic Learning Enables Self-Evolving Agents

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.794011Z

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Observation a7871984-f5a3-4196-b4d6-68d2bdb69a24 · outbound

This paper cites Automated Design of Agentic Systems.

Aviary: training language agents on challenging scientific tasks Automated Design of Agentic Systems

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.798430Z

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Observation 3c630583-13f3-4b5b-ad2b-a82683c5dff1 · outbound

This paper cites Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP.

Aviary: training language agents on challenging scientific tasks Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.802953Z

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Observation fa18ea2a-1474-42ad-972b-e764df186b12 · outbound

This paper cites DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines.

Aviary: training language agents on challenging scientific tasks DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.807216Z

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Observation d4f2e0c0-50b6-4053-a906-3eda5006e3f7 · outbound

This paper cites DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines.

Aviary: training language agents on challenging scientific tasks DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.811362Z

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Observation 3023874f-f2ca-4513-9901-7f7f440f7178 · outbound

This paper cites OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models.

Aviary: training language agents on challenging scientific tasks OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.815470Z

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Observation a00bc530-8f2f-41a3-b7d9-239626c32029 · outbound

This paper cites MLAgentBench: Evaluating language agents on machine learning experimentation.

Aviary: training language agents on challenging scientific tasks MLAgentBench: Evaluating language agents on machine learning experimentation

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.819746Z

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Observation 4659a44c-bcf5-458b-9936-4acab57bde96 · outbound

This paper cites DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning.

Aviary: training language agents on challenging scientific tasks DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.823933Z

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Observation bb7cf069-d7b1-443c-990b-b70b2df43756 · outbound

This paper cites Large language models orchestrating structured reasoning achieve Kaggle grandmaster level.arXiv preprint arXiv:2411.03562, 2024.

Aviary: training language agents on challenging scientific tasks Large language models orchestrating structured reasoning achieve Kaggle grandmaster level.arXiv preprint arXiv:2411.03562, 2024

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.832728Z

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Observation 56d67857-42eb-4820-8aa6-a2492a386128 · outbound

This paper cites InfiAgent-DABench: Evaluating agents on data analysis tasks.

Aviary: training language agents on challenging scientific tasks InfiAgent-DABench: Evaluating agents on data analysis tasks

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.836610Z

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Observation 1bf9ba8d-69a4-48c7-b4c2-38176c1245da · outbound

This paper cites Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents.

Aviary: training language agents on challenging scientific tasks Tapilot-Crossing: Benchmarking and Evolving LLMs Towards Interactive Data Analysis Agents

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.840350Z

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Observation 1d70bc40-c869-4731-bde5-9e53b947404c · outbound

This paper cites Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data.

Aviary: training language agents on challenging scientific tasks Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.844508Z

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Observation e4cf5ed5-2db6-47ff-8eae-239b980e9ca9 · outbound

This paper cites CLadder: A benchmark to assess causal reasoning capabilities of language models.

Aviary: training language agents on challenging scientific tasks CLadder: A benchmark to assess causal reasoning capabilities of language models

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.849087Z

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Observation deec53f3-f762-4f80-a9a5-1c05303d09e5 · outbound

This paper cites DiscoveryBench: Towards Data-Driven Discovery with Large Language Models.

Aviary: training language agents on challenging scientific tasks DiscoveryBench: Towards Data-Driven Discovery with Large Language Models

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.853949Z

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Observation 167c872c-f0ec-430e-be88-7410b3a88833 · outbound

This paper cites Are large language models superhuman chemists?.

Aviary: training language agents on challenging scientific tasks Are large language models superhuman chemists?

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Observation 379f7265-de48-4435-8c6f-dee53f2ad07d · outbound

This paper cites BLADE: Benchmarking language model agents for data-driven science.

Aviary: training language agents on challenging scientific tasks BLADE: Benchmarking language model agents for data-driven science

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.863289Z

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Observation 3c54096d-4cb6-412a-b41c-60c494ac2cce · outbound

This paper cites SciAgent: Tool-augmented language models for scientific reasoning.

Aviary: training language agents on challenging scientific tasks SciAgent: Tool-augmented language models for scientific reasoning

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:07:33.867159Z

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Pith citing papers

Observation 6e7920a1-695e-4797-93dc-24ae6b7955ae · inbound

MDCrow: Automating Molecular Dynamics Workflows with Large Language Models cites this paper.

MDCrow: Automating Molecular Dynamics Workflows with Large Language Models Aviary: training language agents on challenging scientific tasks

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Resolution: unresolved; no resolver link, observed 2026-08-07T21:06:30.848762Z

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Observation f56ce361-8a2a-45eb-8d23-a8927fe21a17 · inbound

EXP-Bench: Can AI Conduct AI Research Experiments? cites this paper.

EXP-Bench: Can AI Conduct AI Research Experiments? Aviary: training language agents on challenging scientific tasks

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Observation 50a5f312-afa9-40d9-9b76-5dd7d780d5df · inbound

On the Comprehensibility of Multi-structured Financial Documents using LLMs and Pre-processing Tools cites this paper.

On the Comprehensibility of Multi-structured Financial Documents using LLMs and Pre-processing Tools Aviary: training language agents on challenging scientific tasks

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URSA: The Universal Research and Scientific Agent cites this paper.

URSA: The Universal Research and Scientific Agent Aviary: training language agents on challenging scientific tasks

Reference 13

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Observation 3aeda90a-29e6-4e03-8d72-c02d391caf9a · inbound

An Auditable Agent Platform For Automated Molecular Optimisation cites this paper.

An Auditable Agent Platform For Automated Molecular Optimisation Aviary: training language agents on challenging scientific tasks

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Resolution: unresolved; no resolver link, observed 2026-08-06T04:32:28.750648Z

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CFDLLMBench: A Benchmark Suite for Evaluating Large Language Models in Computational Fluid Dynamics Aviary: training language agents on challenging scientific tasks

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Resolution: verified exact; arxiv_id, observed 2026-05-18T15:06:32.127790Z

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Observation 99fe328a-9b3b-4d86-af92-ed0a54be5500 · inbound

E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testing cites this paper.

E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testing Aviary: training language agents on challenging scientific tasks

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Resolution: unresolved; no resolver link, observed 2026-08-03T19:10:12.689040Z

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Observation 93d48b52-9dfe-463f-8c33-3f149ba91a3c · inbound

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LABBench2: An Improved Benchmark for AI Systems Performing Biology Research Aviary: training language agents on challenging scientific tasks

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-16T07:17:30.244014Z

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Observation 7896e850-321c-452a-a97f-f0c6ec688625 · inbound

LABBench2: An Improved Benchmark for AI Systems Performing Biology Research cites this paper.

LABBench2: An Improved Benchmark for AI Systems Performing Biology Research Aviary: training language agents on challenging scientific tasks

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T07:17:30.142238Z

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Observation 229c5cf7-7a0c-4482-b783-d12eaa20804d · inbound

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Self-Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale Aviary: training language agents on challenging scientific tasks

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:25:56.381216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 80af3eb4-7e8b-4962-bf57-ab6c6f68151d · inbound

Self-Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale cites this paper.

Self-Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale Aviary: training language agents on challenging scientific tasks

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:29:09.178039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8c23db31-9470-45da-9dda-c40fb2dabac2 · inbound

Self-Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale cites this paper.

Self-Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale Aviary: training language agents on challenging scientific tasks

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-06-30T23:05:07.378614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 59de4aee-980c-4d86-8e67-3d75fe54d948 · inbound

Auto-Configuring Scientific Simulators with Lightweight Coding-Agent Adapters cites this paper.

Auto-Configuring Scientific Simulators with Lightweight Coding-Agent Adapters Aviary: training language agents on challenging scientific tasks

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-03T01:47:32.148419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3de6351f-0f16-4b8a-8297-47fca0297a28 · inbound

Auto-Configuring Scientific Simulators with Lightweight Coding-Agent Adapters cites this paper.

Auto-Configuring Scientific Simulators with Lightweight Coding-Agent Adapters Aviary: training language agents on challenging scientific tasks

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-06-29T15:23:32.991952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.