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Paper Citation Record · LEDGER

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

As of 8 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 11 inbound Pith citation observations for arXiv:2505.16997.

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

pith.paper-citation-record.v1
2505.16997 v1

Coverage vector

measured 72 of 72 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:56:20.169929Z

measured 83 of 83 standing notices

One-hop event checks from named stored sources.

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

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:12:59.939425Z

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

72 of 72 outbound references displayed

  • verified exact0
  • verified fuzzy37
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation e1bd94cc-2b2b-43d0-b96e-b99bf4444784 · outbound

This paper cites GPT-4 Technical Report.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs GPT-4 Technical Report

Reference 1

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no resolver link, observed 2026-08-07T14:56:12.950934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:12.950934Z digest=sha256:928403863dcf929481505046ec6b9a3ed4353333648514a67746da1853b48546

Observation 8c67f104-4051-4df1-9bda-796e6e07700f · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 2

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no resolver link, observed 2026-08-07T14:56:13.094048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:13.094048Z digest=sha256:a29af72790a28376962dcb305d7874c3f10a9d5c71c194a9bbe45a3292e55254

Observation bf1239fb-4081-4440-ab78-5176f4eabc48 · outbound

This paper cites Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:13.385647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:13.385647Z digest=sha256:7f30e7f2b63e13b87f8966e6602b409cb70562a7a11729fded22481ca900c954

Observation 3532ae06-f22d-4dcf-bdb5-1d26d8ca71a8 · outbound

This paper cites Factscore: Fine-grained atomic evaluation of factual precision in long form text generation.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Factscore: Fine-grained atomic evaluation of factual precision in long form text generation

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:28.076017Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:13.520582Z digest=sha256:64f322e2ccc870f6728136b186fa0a801f063aa3b6f42fe9de44f274da7d726f

Observation 5149f40a-1b30-48f0-ac8c-35f680f397d2 · outbound

This paper cites MAS-GPT: Training LLMs to build LLM-based multi-agent systems.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs MAS-GPT: Training LLMs to build LLM-based multi-agent systems

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:27.953582Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:13.659203Z digest=sha256:01b3cd807ce342c4d8c9ab7e781165548430f387a9f744bf510abc3ca04db0d6

Observation ba4da8b6-77a4-4785-a73b-61772d402c46 · outbound

This paper cites Chatdev: Communicative agents for software development.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Chatdev: Communicative agents for software development

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:27.688239Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:13.831157Z digest=sha256:f9defa89f0d716589e21d4ac3fa4fdf74a7ce96cf2216fbc51df3cbdb422d0e5

Observation 88199a62-d141-44f3-acd7-fb5455d6ec78 · outbound

This paper cites Towards an AI co-scientist.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Towards an AI co-scientist

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:13.962802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:13.962802Z digest=sha256:79daf1e275c7a334fab158abddfa380bcc31aefd3868bb7aa945daf2220e29f7

Observation b7a056cb-406a-4d9d-b677-83c5e9be5e37 · outbound

This paper cites Metagpt: Meta programming for a multi-agent collaborative framework.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Metagpt: Meta programming for a multi-agent collaborative framework

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:27.525390Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:14.127780Z digest=sha256:0dd6dff3551371c82bc4ee621ab8cc926d1246302c6154acf214f333b76431dd

Observation 1ff3545c-988e-41a3-9e45-eee35e822c11 · outbound

This paper cites Macm: Utilizing a multi-agent system for condition mining in solving complex mathematical problems.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Macm: Utilizing a multi-agent system for condition mining in solving complex mathematical problems

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:27.319870Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:14.252079Z digest=sha256:26c2bf9f83b3a890394e5d60ade852c1578948c751e3c1822dad2b9aa7d1dfad

Observation 43d112a5-86f1-4627-8abd-b5bdd4589edc · outbound

This paper cites A dynamic llm-powered agent network for task-oriented agent collaboration.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs A dynamic llm-powered agent network for task-oriented agent collaboration

Reference 11

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no resolver link, observed 2026-08-07T14:56:14.393877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:14.393877Z digest=sha256:5cbf2c63cf928f351bb27943e22fb1a593402b337f6323871bf84828cab4a60d

Observation 3d84dd75-8f8b-4c81-a378-e35ad8047585 · outbound

This paper cites Autonomous chemical research with large language models.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Autonomous chemical research with large language models

Reference 12

Resolution
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no resolver link, observed 2026-08-07T14:56:14.463701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:14.463701Z digest=sha256:d6633d9f0a6bce7b57f3121640f3d20965c5302f6187714c86de05de487cf830

Observation 3642e7f3-8bd7-4580-8b8d-d1abe3edce3d · outbound

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

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:14.585687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:14.585687Z digest=sha256:373a9ca0cbed967f9a475b5415c99af9564c0dcf4bf15388ad03068d6167d34f

Observation 5f8b6c3d-2c7a-4c79-9c91-a9766e5cf457 · outbound

This paper cites Self-evolving multi-agent networks for software development.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Self-evolving multi-agent networks for software development

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:27.133930Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:14.739396Z digest=sha256:2e800821d21ca666eb3a9ff2b9af7e8bc5ac1e03d3ccfe32d2f16f644c53b163

Observation 1ff88f16-11af-495d-8d73-4ff8313e22ad · outbound

This paper cites Improving factuality and reasoning in language models through multiagent debate.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Improving factuality and reasoning in language models through multiagent debate

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:14.919082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:14.919082Z digest=sha256:b5de4732ff10e752f72c1de14f126c7246800108bf5072911b258c45c69d21e9

Observation 54228d32-20ea-49af-a86e-c896b534b948 · outbound

This paper cites Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:26.871977Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:15.038046Z digest=sha256:4c5c6cb362961de4365fe12e1718dff88199a0f390044564ee19770c42edf555

Observation 22fc8921-5420-4b5a-bf01-41d5a2df7d14 · outbound

This paper cites Groups of diverse problem solvers can outperform groups of high-ability problem solvers.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Groups of diverse problem solvers can outperform groups of high-ability problem solvers

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:26.694205Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:15.123193Z digest=sha256:03770e7ecb955d19dd7f23e11d6e2d8992fc144f696a6469eaf24cba680e3834

Observation d732d899-6d3b-42c5-99b4-863ab49cbcb6 · outbound

This paper cites Cognitive style as environmentally sensitive individual differences in cognition: A modern synthesis and applications in education, business, and management.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Cognitive style as environmentally sensitive individual differences in cognition: A modern synthesis and applications in education, business, and management

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:26.506457Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:15.239641Z digest=sha256:d4c385e87daed03c90e0a94833c8d9c6a6814e3c2f04fca37b271de55382d08e

Observation 16c97eb0-7f84-4adb-b45a-fe13c38527c7 · outbound

This paper cites Cognitive diversity, collective intelligence, and learning in teams.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Cognitive diversity, collective intelligence, and learning in teams

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:26.301833Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:15.329682Z digest=sha256:4a81135766b2c657420ca060a4e5fdb134cb43b341ee9cdd3c54138df257dfae

Observation 73cca058-bfd3-4c04-92a8-1bd9ed429c94 · outbound

This paper cites Qwen2.5 Technical Report.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Qwen2.5 Technical Report

Reference 20

Resolution
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no resolver link, observed 2026-08-07T14:56:15.492500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:15.492500Z digest=sha256:b7dc065b6beb9740bc1ad341bc32febdfc432e32745020af8d6b2a4c1269e915

Observation fd49d9b7-e81c-4c2f-b775-c537afe546c4 · outbound

This paper cites The Llama 3 Herd of Models.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs The Llama 3 Herd of Models

Reference 21

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no resolver link, observed 2026-08-07T14:56:15.666814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:15.666814Z digest=sha256:311cc0a1288ef8e2c615398ff98d9c578c44c9ed95dd553fa91df17120ad8c20

Observation 4bf57dbc-c0ac-405b-b92d-fc51bffb92ce · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 22

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no resolver link, observed 2026-08-07T14:56:15.859990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:15.859990Z digest=sha256:d24ed4180b434ae3b51dab58af0d73a0c5914f55b0fefe1644a17b71350e7801

Observation e9e3eb3f-3f10-494d-b5e1-2eb764672729 · outbound

This paper cites Self-refine: Iterative refinement with self-feedback.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Self-refine: Iterative refinement with self-feedback

Reference 23

Resolution
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no resolver link, observed 2026-08-07T14:56:16.007804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:16.007804Z digest=sha256:6d73844f00491342cba52005afc53121ddc48a5abae0c1eeca411e1a686f1f78

Observation 9856dbcf-8260-4dc4-bf8c-36d22dde4ecf · outbound

This paper cites Scaling large language model-based multi-agent collaboration.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Scaling large language model-based multi-agent collaboration

Reference 24

Resolution
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no resolver link, observed 2026-08-07T14:56:16.158573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:16.158573Z digest=sha256:6b7e4dbc5a63497201cdc1cc9a18cdb0aa065575a717f0b5b521778123723432

Observation 92536cbe-cef3-4b47-b376-0609acc6a87f · outbound

This paper cites Encouraging divergent thinking in large language models through multi-agent debate.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Encouraging divergent thinking in large language models through multi-agent debate

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:26.058077Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:16.343171Z digest=sha256:447d608214ffabd4ffc4db1bb08b9936e47740055bc5aa6b1364da4d182e30fa

Observation 5fe8adf3-ccf5-46b8-b4f7-323cc3f23464 · outbound

This paper cites Mapcoder: Multi-agent code generation for competitive problem solving.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Mapcoder: Multi-agent code generation for competitive problem solving

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:25.892785Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:16.545902Z digest=sha256:884a30ca4fbe9fcd9979fbee2027dbad78e319e02cdd2b89b32d4adef10aaa11

Observation 67181ac2-b86b-4b09-a240-3e368401dca5 · outbound

This paper cites Measuring mathematical problem solving with the math dataset.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Measuring mathematical problem solving with the math dataset

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:16.641702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:16.641702Z digest=sha256:338675fd57dc43d6d86b9902124b45f3ea8c2bc4ebf248e534d7bcdc841fd4ca

Observation 1787364b-8022-4bff-8506-a43967a5b2f3 · outbound

This paper cites Automated design of agentic systems.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Automated design of agentic systems

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:25.764326Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:16.756064Z digest=sha256:4cb53a92b54cd418b0d3d254291a84ed52d5b864f8807e9cc766b812f7a2d666

Observation 93eade86-d82b-467f-aa46-7b6b98a26fbc · outbound

This paper cites Less is more: Using multiple LLMs for applications with lower costs.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Less is more: Using multiple LLMs for applications with lower costs

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:25.523147Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:16.874587Z digest=sha256:4e851ce4ac9f223e70af00569a9353621da578fb4443556e16d61054dc85c56a

Observation 3b63b271-586d-4d89-b813-dad77ffb6e01 · outbound

This paper cites CollabStory: Multi-LLM Collaborative Story Generation and Authorship Analysis.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs CollabStory: Multi-LLM Collaborative Story Generation and Authorship Analysis

Reference 30

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no resolver link, observed 2026-08-07T14:56:16.987442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:16.987442Z digest=sha256:a83fbc65dada7c4618e8c374352c65ab06c92523d7073d14055cb95478232352

Observation 0fa5ef8e-e702-436c-9719-bd1660e6ada1 · outbound

This paper cites Llm-blender: Ensembling large language models with pairwise ranking and generative fusion.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Llm-blender: Ensembling large language models with pairwise ranking and generative fusion

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:25.292594Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:17.044992Z digest=sha256:eef7e5198d5af2f0a57988f84e7bba9dfb5f92b57ff495e31df8fe47cd3cf84e

Observation b15b70bb-5315-40b8-8754-0039bebf16e2 · outbound

This paper cites Mixture-of-agents enhances large language model capabilities.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Mixture-of-agents enhances large language model capabilities

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:25.110130Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:17.120948Z digest=sha256:b9105663749ac540ff8531b9769f09123744925dafa2b486ba3b57e9ee67d6a4

Observation bf854170-7f33-4f87-a6e1-e30049418d3a · outbound

This paper cites Reconcile: Round-table conference improves reasoning via consensus among diverse llms.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Reconcile: Round-table conference improves reasoning via consensus among diverse llms

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:24.917779Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:17.198192Z digest=sha256:2c888d8b695ef50d80f8e765bf51703bb121583c9681279bb4bd0e2190e6671c

Observation c885b066-ba05-4f35-8790-977fb7e04a8b · outbound

This paper cites MasRouter: Learning to Route LLMs for Multi-Agent Systems.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs MasRouter: Learning to Route LLMs for Multi-Agent Systems

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:17.289868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:17.289868Z digest=sha256:92df8776270baf8927e8ba25247f91ef63bc40a1c92ab51c7b0a395e0d035917

Observation 8592dca8-5183-4e6f-96e7-6ab3ccf6a063 · outbound

This paper cites Swe-bench: Can language models resolve real-world github issues? In The Twelfth International Conference on Learning Representations, 2024.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Swe-bench: Can language models resolve real-world github issues? In The Twelfth International Conference on Learning Representations, 2024

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:24.804763Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:17.354402Z digest=sha256:dc14eb366d387f48dfe8adee3cb1f59a5347741428c934c92447d737fb4e6cff

Observation 45235036-775a-462a-8036-5fbb352037d8 · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 36

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unresolved
no resolver link, observed 2026-08-07T14:56:17.427258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:17.427258Z digest=sha256:0f35e2fde6f4b506af9e7bc79c02716835a799d80b0a27c01ddc1cedca9461a5

Observation 7039e55a-abaa-4b5b-a919-638a3732ebf8 · outbound

This paper cites Introducing healthbench.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Introducing healthbench

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:24.588469Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:17.493932Z digest=sha256:baec5b7f0d1307cf4bfd248caf3334992ebedca315a4cd211b3ab7792148fc99

Observation 61f62060-dac7-4daf-89b3-263bf2a875a8 · outbound

This paper cites Pixiu: a large language model, instruction data and evaluation benchmark for finance.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Pixiu: a large language model, instruction data and evaluation benchmark for finance

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:24.361448Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:17.581084Z digest=sha256:07c7ecf15f4e1ea61e637d9daf605623add5df9b9395371598b6a5bb43d9d373

Observation 32d64737-d2e5-4d59-8114-15e077e82a80 · outbound

This paper cites Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:24.175769Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:17.669761Z digest=sha256:56a2494731a47ca6eddfc05384fc8af19835c8be6a5eb7d468ef3918748a5cf1

Observation 7a140101-cb25-4fb9-ab36-9620dbbd50b3 · outbound

This paper cites Judgebench: A benchmark for evaluating LLM-based judges.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Judgebench: A benchmark for evaluating LLM-based judges

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:17.715014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:17.715014Z digest=sha256:796451be5186d82517068e6cc71a722461947b356f5ed34b005663b7c0a63c73

Observation 7378a532-c655-434d-b390-565fd30d50e2 · outbound

This paper cites Mistral-7b-instruct-v0.3.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Mistral-7b-instruct-v0.3

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:23.988035Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:17.765525Z digest=sha256:91b67533555c3485712e094d3a6d5d92747ff6a63fff6e59ca19fcf40a849034

Observation f931654f-aa19-479f-a8f5-314a995b9a49 · outbound

This paper cites Mistral-small-3.1-24b-instruct-2503.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Mistral-small-3.1-24b-instruct-2503

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:23.741812Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:17.860902Z digest=sha256:8ab58c22225fc0416b9d3068d63698d7cb79b8efefd7eafe9c0daa8acbf3c6f3

Observation c0b110d7-d02e-43fe-8ba6-466fd1d4db17 · outbound

This paper cites Qwen2.5-Coder Technical Report.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Qwen2.5-Coder Technical Report

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:17.927682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:17.927682Z digest=sha256:5cb7657aa803ae9a0998f5b73dc3a0f70b503e4c75311e2c5ca0df4012ae1884

Observation 53fbc1bd-69b7-491e-a25d-0a0ecd31a65f · outbound

This paper cites Developing chemdfm as a large language foundation model for chemistry.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Developing chemdfm as a large language foundation model for chemistry

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:23.448656Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:18.011140Z digest=sha256:6af7779c7c30905402249c4e4ac7578762cf17bd0312edd70622efce30f8c815

Observation 388f5004-f7fd-42fd-aa3f-875472ee7a79 · outbound

This paper cites Sciphi-mistral-7b-32k.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Sciphi-mistral-7b-32k

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:23.063346Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:18.056466Z digest=sha256:2ef25550f30b564f8c7bb49bdfe5447411cffcbd1cb6422f24a6e2e966b70e68

Observation 48b074f4-260f-4803-a308-e9882c1bbdc6 · outbound

This paper cites Llama3-xuanyuan3-70b-chat.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Llama3-xuanyuan3-70b-chat

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:22.811321Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:18.157839Z digest=sha256:aec0dd3ed641941380a4d672564199055c6acf811cc70b9d72d7c4121e6d91f3

Observation 97795c31-42e4-4a17-a938-6d47cfbef5c5 · outbound

This paper cites Zhilu-2-8b-instruct.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Zhilu-2-8b-instruct

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:22.477046Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:18.239602Z digest=sha256:7b2541c9bdd093003dffa55b1e71cc733535e5a46c31c5888dd6a30f3f89b929

Observation 74572775-f553-4d80-b591-d13b0bfcbe01 · outbound

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

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:18.300778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:18.300778Z digest=sha256:8e9fd5c7e807ccecf45d48f4235f6506e2e239035b5ef71032fc590085b179e9

Observation 0c54b62f-0d57-4e6f-abdc-fa3763194e6a · outbound

This paper cites Qwq-32b: Embracing the power of reinforcement learning, March 2025.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Qwq-32b: Embracing the power of reinforcement learning, March 2025

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:18.353587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:18.353587Z digest=sha256:e3b508f41acdc62efcebef3f4d9e2854c01d467a7118eb9f5c8721a4fb8b7523

Observation bc82ec2e-a322-4f9b-bebc-268086e7fa4f · outbound

This paper cites Open Thoughts.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Open Thoughts

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:18.426104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:18.426104Z digest=sha256:5a0c008a0ea48813f777857ec1095fc1ac3cc26c3d2b9fbf6c115f9d3c0cf903

Observation 9f289a62-e54f-491f-805c-4b16c33daf91 · outbound

This paper cites Program induction by rationale generation: Learning to solve and explain algebraic word problems.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Program induction by rationale generation: Learning to solve and explain algebraic word problems

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:22.322992Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:18.487704Z digest=sha256:e576f47068ee1915e36e6c780a458b16eb1a620b037fbbf6fa64f366603bc9fe

Observation 623ad1e0-a422-4864-a833-f9838bd8de86 · outbound

This paper cites Pal: Program-aided language models.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Pal: Program-aided language models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:18.582867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:18.582867Z digest=sha256:4fac0baa187f7200dce1904545143b39979d3495ac968ca0528f804a3d1679be

Observation cc74f0ac-f4b5-4356-a7fe-21e96d54b07a · outbound

This paper cites Aime-2024.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Aime-2024

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:21.986194Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:18.678281Z digest=sha256:f2e338ee0328b1c7209c9281a05fa0a6d2f6b3e75cbf879554b23862de9b7535

Observation a9537493-538a-4b25-95c2-d0e0d6cfcbde · outbound

This paper cites Measuring massive multitask language understanding.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Measuring massive multitask language understanding

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:18.745409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:18.745409Z digest=sha256:ecee4270bba5baf7dbf9b96461ca34c4f955593e81fd7f340df3f8c92a7c39a8

Observation 001c3634-310c-46ea-92c5-7742de7d2840 · outbound

This paper cites MMLU-pro: A more robust and challenging multi-task language understanding benchmark.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs MMLU-pro: A more robust and challenging multi-task language understanding benchmark

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:21.807179Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:18.800380Z digest=sha256:1f1472770c173ad25e05f6b3bdd50ced27bc16ce8faf054ecc87ebf0ac2216e7

Observation 6f343a77-5bae-4b11-960b-cd7328470781 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Evaluating Large Language Models Trained on Code

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:18.856269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:18.856269Z digest=sha256:877ccbe04e39abf093034e7c968b26df8b7b0ba6503c50d6f411f9a5f5d46f67

Observation 2deb4640-c132-41db-9ee7-022260c8860b · outbound

This paper cites Program Synthesis with Large Language Models.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Program Synthesis with Large Language Models

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:18.923843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:18.923843Z digest=sha256:43563392bee71fd3d61b7cc867935f72557669d7f72a6e811483a0d15ff8ac40

Observation 0af168d1-adda-489b-abfd-8bfab6a0c681 · outbound

This paper cites Is your code generated by chatGPT really correct? rigorous evaluation of large language models for code generation.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Is your code generated by chatGPT really correct? rigorous evaluation of large language models for code generation

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:18.988619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:18.988619Z digest=sha256:a18c7fd0c1801b17f8842df152ae52328aeb563931a852a60c200c211014abc0

Observation 777e1df8-fdb1-47e2-9829-3bdc38f3ffb3 · outbound

This paper cites Scibench: Evaluating college-level scientific problem- solving abilities of large language models.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Scibench: Evaluating college-level scientific problem- solving abilities of large language models

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:21.656683Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:19.034330Z digest=sha256:ecd50834465eaf73a081cf59622ca2ef3e89f6e7c067dcc5c0e2d7d3bb8e8a66

Observation efe5d50a-0dd7-4c89-a13c-c98f85acb07f · outbound

This paper cites Scieval: A multi-level large language model evaluation benchmark for scientific research.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Scieval: A multi-level large language model evaluation benchmark for scientific research

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:21.503402Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:19.117754Z digest=sha256:503677a63b4063dce3bb6691839ac528b9a476cba0d79c1852f592dd174eaeed

Observation 033ffbba-dc08-4792-b726-e61d3ce34555 · outbound

This paper cites Sciknoweval: Evaluating multi-level scientific knowledge of large language models.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Sciknoweval: Evaluating multi-level scientific knowledge of large language models

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:19.192621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:19.192621Z digest=sha256:61babaf3cb38acdd76c838d7519a21aaf6f264490802c01bbd9b3192ae8bfb29

Observation b6b8c028-d67c-4ef5-9e5b-eac0fd7da4cb · outbound

This paper cites Medmcqa: A large-scale multi- subject multi-choice dataset for medical domain question answering.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Medmcqa: A large-scale multi- subject multi-choice dataset for medical domain question answering

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:21.346240Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:19.261687Z digest=sha256:062f8bb4a704eee15ae7fc3ff562b4f1a9664e0941b6b3026301eddc902c360f

Observation 176f82b3-9a87-41d1-9bba-98d1b581b4c9 · outbound

This paper cites What disease does this patient have? a large-scale open domain question answering dataset from medical exams.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs What disease does this patient have? a large-scale open domain question answering dataset from medical exams

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:19.323713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:19.323713Z digest=sha256:b936b2db73b25af0c132f7a5a8d96b07ba933ad57008c2de06597d9172ed4566

Observation 25a0e1c0-5648-4354-b07c-9b154607500c · outbound

This paper cites Pubmedqa: A dataset for biomedical research question answering.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Pubmedqa: A dataset for biomedical research question answering

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:21.167655Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:19.400349Z digest=sha256:03ce3b1a9dc9b8e77bbf80a787eec05341e2ee2fe48d1e6fe9d09b6c74f7a780

Observation 32132789-63dc-4736-8df1-4aff64f30525 · outbound

This paper cites FinanceBench: A New Benchmark for Financial Question Answering.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs FinanceBench: A New Benchmark for Financial Question Answering

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:19.488106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:19.488106Z digest=sha256:14d220ee055564ea6c95c63f6222f0de7b21a11a073ed9704d85db2820ec2ba4

Observation 57d8df30-03e8-4eab-b25e-e6c52a9aab9d · outbound

This paper cites Finqa: A dataset of numerical reasoning over financial data.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Finqa: A dataset of numerical reasoning over financial data

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:19.580778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:19.580778Z digest=sha256:29503cdfe38cd24fd846d0957a0712b241253156b994e85a81b301df6085965b

Observation 456b63be-2a3e-4829-9003-911f4bc8b422 · outbound

This paper cites an unresolved cited work.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Unresolved cited work

Reference 67

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:56:21.023859Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:19.733423Z digest=sha256:d4aeea5869fcd3b4213e8abba642b15ef9fc7346796f819dad3fe6a77f4c77ac

Observation dfb331ff-ccab-41e9-96dd-889666824425 · outbound

This paper cites Aime2025.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Aime2025

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:20.805772Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:19.832316Z digest=sha256:86460678a37c1025981eeac2eec627d42b12b5f6b9faf47f9104e381547ce4f5

Observation f6c6a078-025c-44de-bc9c-4dac425e4d73 · outbound

This paper cites ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:19.901471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:19.901471Z digest=sha256:8475982e23eaeb86901508b4e6ac89b988a03516f1f03d29db27b746316a9b7e

Observation 66e6587a-168d-4315-8abc-c53063c7e9ef · outbound

This paper cites Codestral-22b-v0.1.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Codestral-22b-v0.1

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:20.688926Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:20.011101Z digest=sha256:01ffa00f228134d5bf1be742914f5e68598dab864105eebdcdaca2ee4d1a9d68

Observation 41a05d09-9376-4706-9575-2d7832ebcdc2 · outbound

This paper cites Openbiollms: Advancing open-source large language models for healthcare and life sciences.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Openbiollms: Advancing open-source large language models for healthcare and life sciences

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:56:20.590081Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:56:20.093760Z digest=sha256:e90fb15b066527121a5f326764531d272f9a0b3debb1fc3eb5aa025b6ae29b0a

Observation cdd69850-37bc-4bfc-9052-f6da866a1529 · outbound

This paper cites BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:20.169929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:20.169929Z digest=sha256:201d152180e97cda1d30bf13465f7df592d1f70d2b0140db914d212f92b345d4

Observation 6c514cbe-bf91-4a78-9c22-776779b1d4ef · outbound

This paper cites an unresolved cited work.

X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs Unresolved cited work

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:16.448880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:16.448880Z digest=sha256:dcaaba4e81edf41bd3a69991d32790146a409e2f7c0cf63ab3dea9db1a61b278

Pith citing papers

Observation 3a0deef6-b5a5-46c0-893e-2f70b92aef8b · inbound

How to Train a Leader: Hierarchical Reasoning in Multi-Agent LLMs cites this paper.

How to Train a Leader: Hierarchical Reasoning in Multi-Agent LLMs X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-06T18:12:59.939425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:12:59.939425Z digest=sha256:2822e0b0888aec277a3285cd50fd4b991356d6bafc54636ac2afcbe5f2bdaec2

Observation ee1a5778-d955-436d-8b32-97dfe90e0fe1 · 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 X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 269

Resolution
verified exact
arxiv_id, observed 2026-05-14T22:23:15.331641Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-05-14T22:23:14.621091Z digest=sha256:be71137cc7e791eda3e67a5de59b51bd1e3353c8d307018205bc0f6bb64b1690

Observation 870c481d-cd7e-451d-9223-9629cb0860f9 · inbound

Beyond Sentiment: A Multi-Agent Pipeline for Actionable Business Advice from Reviews cites this paper.

Beyond Sentiment: A Multi-Agent Pipeline for Actionable Business Advice from Reviews X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-16T13:07:54.668119Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-16T13:05:11.907398Z digest=sha256:48093299d181632f50c6f1561fd2a9e958c464c7276df81373a3701c0b7426fe

Observation 7c44401f-ea6e-4758-b0ca-1874ae02f04d · inbound

From Skills to Talent: Organising Heterogeneous Agents as a Real-World Company cites this paper.

From Skills to Talent: Organising Heterogeneous Agents as a Real-World Company X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T19:21:09.515950Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-08T12:05:38.965920Z digest=sha256:42498adb4762fbf95722775219525d2211521397ac215227ece4da64fd347157

Observation de470aa8-f4fa-4362-b476-0517a7a04cb8 · inbound

Heterogeneous Scientific Foundation Model Collaboration cites this paper.

Heterogeneous Scientific Foundation Model Collaboration X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 52

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T04:30:11.028332Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-07T08:50:05.980191Z digest=sha256:7beaf737e3423f5589a6a4d2d587f2c315cfe3a17547725e053d6a9072fbea31

Observation 25fb9b2d-14f6-465b-844f-9af3faa01319 · inbound

FlowCompile: An Optimizing Compiler for Structured LLM Workflows cites this paper.

FlowCompile: An Optimizing Compiler for Structured LLM Workflows X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:49:25.952279Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-05-14T19:48:28.425792Z digest=sha256:ea7a8640b2186086342eff70028a4fa582615639e3342e042b1b316f1743263b

Observation 30815989-28b0-4f59-8c93-c4cafc891c4e · inbound

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems cites this paper.

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 172

Resolution
verified exact
arxiv_id, observed 2026-05-15T03:08:57.839900Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-05-15T03:07:38.232966Z digest=sha256:1b23faead03f858030bf9d0380c1e0e867d0b8e3aa5973bdb7d62f494405388a

Observation e1c8c8b9-5ac6-4656-864a-61492551539e · inbound

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems cites this paper.

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 173

Resolution
verified exact
arxiv_id, observed 2026-05-19T16:52:39.964020Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-05-19T16:51:13.491389Z digest=sha256:22e5fb3e41735ba76686399ce125a7dbaeceb71e68716a20b77d4c4adf443bd3

Observation d68c4a99-50b6-4d58-8fbf-bd22a89f52b3 · inbound

Response-Conditioned Parallel-to-Sequential Orchestration for Multi-Agent Systems cites this paper.

Response-Conditioned Parallel-to-Sequential Orchestration for Multi-Agent Systems X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-20T19:33:42.346287Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-05-20T19:30:13.469451Z digest=sha256:d03b5b470eb24637fc67a95187e8d26eeadbdf9ddd6b7980ea43682f1756db28

Observation 3314c09e-1789-48e1-bc09-abf0887291b2 · inbound

From Model Scaling to System Scaling: Scaling the Harness in Agentic AI cites this paper.

From Model Scaling to System Scaling: Scaling the Harness in Agentic AI X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-06-29T21:33:59.158363Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-29T21:29:57.326718Z digest=sha256:2dba6182557edfc08e7e31bb00129b64e162411bfe1d564db9ce1a94795f0d1c

Observation 51317599-fc8e-4b72-98e3-4c6fb2fd7b45 · inbound

Escaping the Self-Confirmation Trap: An Execute-Distill-Verify Paradigm for Agentic Experience Learning cites this paper.

Escaping the Self-Confirmation Trap: An Execute-Distill-Verify Paradigm for Agentic Experience Learning X-MAS: Towards Building Multi-Agent Systems with Heterogeneous LLMs

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-04T17:19:59.969352Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-06-25T23:49:38.932474Z digest=sha256:b1cc371052f92edd0f861c8029ba8ba8a605c41afba902ecca190fae84231389