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Paper Citation Record · LEDGER

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

As of 18 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 2026-08-17T06:30:58.91139+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:fa944e3900bedd8fff4e9b5e9b893b29e806af2b91bf3579f16496da9b7649bd

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=sha256:813c96c1e88364a4be638cea61e7108c021bead6f6d32b88b447cb3638537a4e

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

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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=sha256:82869587049f35716354bd558f853e9c1e2076b104bd2179f5cd764d5f9062c5

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:13.520582Z digest=sha256:71dfcf0d659429177dca5cfa8a5581535870171f36ceb9642dbdefaa14ffcb7c

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:13.659203Z digest=sha256:ac594a58bdcf8dd5decb62c59779565879336a2a5f85c21a14f8ca29a6943bb7

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:13.831157Z digest=sha256:8a0521aee8b6c5de58b5b3a833b52613454915baccb4431fdf56e5378950b875

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
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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=sha256:7072591c680c651fa213f452c66f27129bc50af1d41c8728bb4825fdcbf9a415

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:14.127780Z digest=sha256:05ecbe6512fccfad6a3a737e4e43ad2148417339af3190c6033c69a60ac65e1f

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:14.252079Z digest=sha256:0448b68142512401d04c322a8a45b685458c198edc8d9a8fdca4b95c61de5e75

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:ff496f9e0fe8c7bec9b3d20ecf517ec2c3cdefb32f0688f0eb0aa9b3920b310e

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

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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=sha256:5e31f0b44875cc4ca0eeea819ad52328ca67fefa0f1dd1de1062a11f68c2d2ce

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=sha256:2ba2a20198a4eac9a2b8d5010312c0d5cd4d0c65aa63dd40fd9a129a73727ba8

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:14.739396Z digest=sha256:fdb6965d801e711f9515087706ecf6b4dba942fe15ecebecb69e9a05191dbc49

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=sha256:35d5472a9234c24f862feeb3247ec3e5b3bb58b65bcd3116bcea5cbd6f4027e4

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:15.038046Z digest=sha256:fd131c7088f85a7bf8720a052325584e824c4d65f6b2c7960745486e41843ae3

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:15.123193Z digest=sha256:c1ef8c71f60bc8dc56d663b8b5145339b59a23e1330540c9664e71df317ea454

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:15.239641Z digest=sha256:69cf3145fbedecb22dfe5323c7d0819ba55b05af4be8df451f2019e0d74341c8

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

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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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:15.329682Z digest=sha256:1d4f7255a286694544f85ec8bc24d3e242bb7e7e157a3c195fd15afcfd1a5582

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

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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=sha256:59dbd4895f36a824837df867bcc0249557d54d0751ee5f8972eff12d9d5afa7e

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=sha256:35629ff3c53787a076f540a6a20411c1d6737aa5b47dca20ad0d89297f0fee7f

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:d305d51742ea49ec17fc0f8fb24c6c27befa9a5255adf10348c451270c8b9f16

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:56:16.007804Z digest=sha256:5a86c01f00c7adfa7f8ffd1a00d1328e8b0921aea2e18a2c88db208909c3b4e9

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=sha256:04d9e186b078da541fc5af2e087cd891cfca4e09a23b5732c2c1be47b37b9f5d

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:16.343171Z digest=sha256:db9088d8eb69b9714117c9b901b02c1655aad2d00e5401a54810b6ebce4d6a47

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:16.545902Z digest=sha256:819da44c5cbee15edbdad9c0df09f613349c4edc653ba700d9c8d721c731a161

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

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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:a70e6c99efdf78cda7ca7b6cf5d3ce9853587583ac03f773dbf6793a31b1fea2

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:16.756064Z digest=sha256:783cbac8b856eadad2a64edec7fc384d7bddffd7ad2b7034658a487e1eaf1402

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:16.874587Z digest=sha256:a7210c3005b6ccf084242441c67bd6229b4d17d84fd1ab524318ef302fcc91b6

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=sha256:798292693c012ad29ba63c73a9ace8b70d0ffec6689efe6d2ba9cce2338b87e6

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:17.044992Z digest=sha256:a9b5b343086481156c4e20445831ac5e83516f5b495009efdf30b45ffe9d15b5

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:17.120948Z digest=sha256:c586d46192ec8964867fe85095d6948c29b2ee88aae0cc849d93d8b7557e97ac

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:17.198192Z digest=sha256:d0da33645a3e73d126b6a6dcd1de48088ccc6a4a165c234fe68dd4108bc110f5

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

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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=sha256:444a12d55de6a90e9f1e0be73b863cbd65065619fe93aeac2d3e8d5c3275491e

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:17.354402Z digest=sha256:1c538b9175dc30df92be452f69fe60bad1fc13c4c9a3871a8e43e7989df61e93

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=sha256:6eda9f9148f36e9194db85a036c55daa7b00126561247f219eaecd5c541cb8c8

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:17.493932Z digest=sha256:6322802eb521122ef779393fdc1f3b02e86101102c625f34b6609e9e9d763439

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:17.581084Z digest=sha256:0dfd0919755e3ca724b42fc69e714de38b41eb2b79f6e1f0bf269f672c383eaf

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:17.669761Z digest=sha256:43ffcd7e342a6bc5f6822a546fa9e90a903a2549b409cbebe619c61338e3ad80

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=sha256:9dad9ffad09a75a706510b993dd0fd4c481111f07d12aa29470c66c29eb25eb3

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:17.765525Z digest=sha256:2e064c8c1e7d59452e56d3fbe487d9f917e39fb9ba780b61b60568c835cdf225

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:17.860902Z digest=sha256:56ffb2dde46507f055a7f2648df64b7ef58a24c174aa3a602cf6bd1e377c6eb9

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=sha256:1ddf8c64a12f642fcc7b4130223a1a07d99a7beb1382bad17ec03d12e4e6fc4c

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:18.011140Z digest=sha256:7ced8b75f4be999b11622c072853319e635b00b15c7590367023e0bbffa87a88

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:18.056466Z digest=sha256:69ecec464d096ba18503f28cb649fd0854980d80fd13cde8ba6418b23418db4d

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:18.157839Z digest=sha256:c9bbb1b4ba341b075ccd90235f175a563ec7c4e2ceae5e2274bcfb67fc4e5a21

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:18.239602Z digest=sha256:09d78d4fd8758eee29a955b0c6af3742affae486e700eb30d0068f658d309e4c

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=sha256:370aad99afeeab64bb85a942e45e4bc82181f0e8d7e7483890b0ec36eb8efbbd

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:d9635d9e524accbb00e416de05ec7edf6ae48add6125d6eda1b379e379444661

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:fb2d859a9e67b4116f14536b0abccbe7eea48e6dae10847677b71c562a84eb67

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:18.487704Z digest=sha256:beffe4f7c76fb47d05731b4d8032abb0f8c71ab020d6b185b31e90ab8871474a

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=sha256:52b5d2ee516c63e8fe8f0946ea05c72cf283d11e0ce7d8e6fe15561b718d2195

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:18.678281Z digest=sha256:b15faab74482e8b4ffb1f7165b2959a5a7c56f7c65ebea60782fcf11426ddf35

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:d88a7ef36a97959a04f613867b545e88bbadedf09150931ac25c644e509bc190

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:18.800380Z digest=sha256:85ccd826ac98ca57c4357bf740071c5b22c840a40447d4e06b9b969f568f6831

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:b4fca28cf2cebdf7036790d9a5e84f18670afffb5a1292f4a27c118bb5d53bd1

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:c4886889c482bce83e8e36383ca166bfee4c16d239d611fb7f5bcd6bb2b63236

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=sha256:8bf7c28be5ee1d77aa01584fbf3341e615f693e328c1b5f1ecf03b55dac54b89

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:19.034330Z digest=sha256:973857e44016c12a656d065e76c8b4cabb24ccc1706e8888e2ba77ce01d113a3

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:19.117754Z digest=sha256:6c84d773a94dc5d882407e2fa050ab8ce1e91fb8cf573790557f202c87dbe514

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:aa477c5858b69749e1befd480f43668709b893108a2bf388e6902973b28b3fa6

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:19.261687Z digest=sha256:42af16c376f80ff2fb13cea4152652fe446dddf8eed7d26eab33c6db0a8a297e

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:bb0cd44be47244e5c894d163cf9a65ea022c9c58c6de54165046b4628ab6c7cc

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:19.400349Z digest=sha256:642c26e8e37ab0cde2acc1c6e1aa736880e68d5b3dfe371aa1b71a4b971b25ed

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=sha256:5ebcef1fc9fb2edc8990394d85c04ab286a7b8fcd538a07286b69a697072626f

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=sha256:0a9534c94a7aa840422d34ae816739c2dcff562740de78fec8ee30c839d6572f

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:19.733423Z digest=sha256:0bb37d9f9713e992738c1faf9979dc5a2b970dea811708ffced2803cfe5a82d7

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:19.832316Z digest=sha256:5c99a649f56ee377f19bb0b970e74a19c33a8a8e3c6d9b9e8cbc17128caffe09

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=sha256:38c36ecaba01ccc7c246b3f07ced69a0b03039502a8cfb005afe247c82e1c467

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:20.011101Z digest=sha256:c819cc53d328d4a878bf8aa3bc0d4296190fe925252200d0b54538345186d2f5

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-07T14:56:20.093760Z digest=sha256:92d852549ca60e4fb7cb82ad7a59a42ec1aa6300e7a7e4b75281ca0855794f99

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=sha256:0da0dbb2510f1158d6e74bcd1e9c24f6b162e12b3448538acefa3e709ebb972d

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:dee91a9ddc072c6567418bd1575235ecd9dcd361a7bb519a58eb0b3022611131

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=sha256:16641282ea613e59fc1ae3f496ea9eeb0a4cb1dbe60b7433ca194640b9491ab5

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-14T22:23:14.621091Z digest=sha256:a0f13e7185f2c697a1b634b659c0065ce7b21fb9aa0c49d66713f0a28153c2f7

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-16T13:05:11.907398Z digest=sha256:8a0d147fef4b62bf6f292c3300cb940df9842752d002401e509c568b2616454a

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-08T12:05:38.965920Z digest=sha256:74c513b2a6be2a6d166623dc3a42ce4b32964534d31436d6b8d9b0115001810b

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-07T08:50:05.980191Z digest=sha256:bbc917f68dd9e188d8ed413936cd8239890401272e7e40ed424a8faa2707f3f5

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-14T19:48:28.425792Z digest=sha256:da6388ef54b0b1c86df44835be246be21cc7d7e02ec5e15a633d220c6b4b1353

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-15T03:07:38.232966Z digest=sha256:ff764396dfbb1abf65ea95f5e5ed53f2a29c2d06b91c634964974385ef6858af

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-19T16:51:13.491389Z digest=sha256:57d4d68311218ccf908c506ab05fcfacf88bdbb371b908204131bfd0122ff81f

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-20T19:30:13.469451Z digest=sha256:ea9d73e729e3193dcb701c95bdb51daff4536a3b754ef8c0f27e641d70a454b2

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-29T21:29:57.326718Z digest=sha256:3551a8c81898e58f93f231e17a450d979c466f06971b5f545fc558f0daa8d1f3

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-25T23:49:38.932474Z digest=sha256:d506ec9ae52e34a95e43e21a705f7054cdaa1656cf4aa7ce8e2e09dd3ad77758