Paper Citation Record · LEDGER

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

As of 10 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 13 inbound Pith citation observations for arXiv:2506.14728.

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

pith.paper-citation-record.v1
2506.14728 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:13:41.081140Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T13:41:59.147784Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:39:50.583619Z

Reference resolution

52 of 52 outbound references displayed

verified exact2
verified fuzzy9
unresolved41
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c47fe6fb-562c-4de0-8aac-0a6a5c27eca8 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Distilling the Knowledge in a Neural Network

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:34.046574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb1e1f3f-01c1-4aff-89d8-618a295b99b4 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:34.154762Z

Source-reported events for the cited work

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Observation 9b38405d-135d-4eb8-af14-40f04c586881 · outbound

This paper cites Patient Knowledge Distillation for BERT Model Compression.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Patient Knowledge Distillation for BERT Model Compression

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:34.333057Z

Source-reported events for the cited work

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Observation feab6543-dc02-436a-9418-2ff401b5f011 · outbound

This paper cites TinyBERT: Distilling BERT for Natural Language Understanding.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes TinyBERT: Distilling BERT for Natural Language Understanding

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:34.496625Z

Source-reported events for the cited work

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Observation c292c6f2-37e3-4c60-8566-692fb0130774 · outbound

This paper cites Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.Advances in neural information processing systems, 33:5776–5788, 2020.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.Advances in neural information processing systems, 33:5776–5788, 2020

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:34.647744Z

Source-reported events for the cited work

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Observation 83eb7cac-4b89-4da7-b39f-a5780946122b · outbound

This paper cites MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:34.807151Z

Source-reported events for the cited work

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Observation 4c853567-8e2b-49f7-a6ac-aaeb6d06d783 · outbound

This paper cites GKD: A General Knowledge Distillation Framework for Large-scale Pre-trained Language Model.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes GKD: A General Knowledge Distillation Framework for Large-scale Pre-trained Language Model

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:35.022808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a784fce5-b071-4cb1-acd7-c4d772b27063 · outbound

This paper cites Large Language Models Are Reasoning Teachers.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Large Language Models Are Reasoning Teachers

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:35.227419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 891b6600-a31c-489a-908d-0e5f9b141caf · outbound

This paper cites Distilling reasoning capabilities into smaller language models.Findings of the Association for Computational Linguistics: ACL 2023, pages 7059–7073, 2023.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Distilling reasoning capabilities into smaller language models.Findings of the Association for Computational Linguistics: ACL 2023, pages 7059–7073, 2023

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:35.387261Z

Source-reported events for the cited work

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Observation 55fbda0d-6636-4dc9-97e0-9359a8b58afd · outbound

This paper cites Symbolic Chain-of-Thought Distillation: Small Models Can Also "Think" Step-by-Step.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Symbolic Chain-of-Thought Distillation: Small Models Can Also "Think" Step-by-Step

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:35.505844Z

Source-reported events for the cited work

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Observation 0cf34416-9442-4a7d-af8c-865bf438c4a4 · outbound

This paper cites Explanations from Large Language Models Make Small Reasoners Better.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Explanations from Large Language Models Make Small Reasoners Better

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:35.654099Z

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Observation 58262a93-84e9-4392-ba4e-8089c71c5556 · outbound

This paper cites Keypoint-based Progressive Chain-of-Thought Distillation for LLMs.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Keypoint-based Progressive Chain-of-Thought Distillation for LLMs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:35.793826Z

Source-reported events for the cited work

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Observation 2a6b8ecd-3139-48df-9533-36419677a6dd · outbound

This paper cites Structured Agent Distillation for Large Language Model.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Structured Agent Distillation for Large Language Model

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:35.958845Z

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Observation cb61dce6-e024-4972-b3cd-1253fc7ba4e3 · outbound

This paper cites Distilling llm agent into small models with retrieval and code tools.arXiv preprint arXiv:2505.17612, 2025.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Distilling llm agent into small models with retrieval and code tools.arXiv preprint arXiv:2505.17612, 2025

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:36.114206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0281c93-37c8-4c9f-a42f-59d15e3596cf · outbound

This paper cites MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:36.272245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bf58615-9a2b-4f50-8897-8d1fa84422d8 · outbound

This paper cites Sub-goal Distillation: A Method to Improve Small Language Agents.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Sub-goal Distillation: A Method to Improve Small Language Agents

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:36.374303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a394f9d-bfd7-46fd-9c18-ce08ad94db00 · outbound

This paper cites Introducing the model context protocol.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Introducing the model context protocol

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:13:45.549466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 69ed8d5b-22f9-4e8f-9f48-916b0e16c637 · outbound

This paper cites Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:36.663271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d970619a-9907-43b5-8c64-7531c88fe872 · outbound

This paper cites Mcip: Protecting mcp safety via model contextual integrity protocol.arXiv preprint arXiv:2505.14590, 2025.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Mcip: Protecting mcp safety via model contextual integrity protocol.arXiv preprint arXiv:2505.14590, 2025

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:36.779013Z

Source-reported events for the cited work

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Observation 6eb47a7c-dab2-4f4e-a89a-3a3cf2d421ec · outbound

This paper cites Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:36.922278Z

Source-reported events for the cited work

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Observation d0cc2725-659f-43ed-81af-a7bc4c14db95 · outbound

This paper cites Alpaca: A strong, replicable instruction-following model.Stanford Center for Research on F oundation Models.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Alpaca: A strong, replicable instruction-following model.Stanford Center for Research on F oundation Models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:13:45.242869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f6d1fc01-67db-426b-8b1a-e0d5c71247bc · outbound

This paper cites Orca: Progressive Learning from Complex Explanation Traces of GPT-4.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Orca: Progressive Learning from Complex Explanation Traces of GPT-4

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:37.195721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bfbdf59-b78a-47f6-8dd4-987c8ea142d5 · outbound

This paper cites Super- correct: Advancing small llm reasoning with thought template distillation and self-correction.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Super- correct: Advancing small llm reasoning with thought template distillation and self-correction

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:13:44.914845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 89e91865-13aa-42c3-a132-9c4650471936 · outbound

This paper cites Learning to Maximize Mutual Information for Chain-of-Thought Distillation.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Learning to Maximize Mutual Information for Chain-of-Thought Distillation

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:13:42.642732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation af3ce0f4-1eb5-4a29-a41a-b445202ece30 · outbound

This paper cites SCOTT: Self-Consistent Chain-of-Thought Distillation.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes SCOTT: Self-Consistent Chain-of-Thought Distillation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:37.673295Z

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Observation d0a7bef4-9d7f-4a31-ae40-eb5e419f8910 · outbound

This paper cites Skip-Thinking: Chunk-wise Chain-of-Thought Distillation Enable Smaller Language Models to Reason Better and Faster.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Skip-Thinking: Chunk-wise Chain-of-Thought Distillation Enable Smaller Language Models to Reason Better and Faster

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:37.810334Z

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Observation 9ac12107-4011-4a08-a43f-6fcdd513b5e9 · outbound

This paper cites ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:37.937008Z

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Observation f10de3b3-cf47-4236-865f-1219861123a4 · outbound

This paper cites Unicott: A unified framework for structural chain-of-thought distillation.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Unicott: A unified framework for structural chain-of-thought distillation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:13:44.641417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e1e73f3d-37d2-4fc7-a746-3bdba3fb80a5 · outbound

This paper cites DISCO: Distilling Counterfactuals with Large Language Models.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes DISCO: Distilling Counterfactuals with Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:38.229405Z

Source-reported events for the cited work

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Observation c09af58c-2728-42d0-87b9-1f6df2bcf652 · outbound

This paper cites Specializing smaller language models towards multi-step reasoning.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Specializing smaller language models towards multi-step reasoning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:13:44.496702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fda6bd76-14b3-4ca1-ba50-712198c84b62 · outbound

This paper cites Learning by Distilling Context.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Learning by Distilling Context

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:38.518193Z

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Observation f324b8e3-faf4-4f7c-b7ae-0e6e587678e9 · outbound

This paper cites Efficient llm context distillation.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Efficient llm context distillation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:38.694864Z

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Observation c18673d4-5a6e-4120-8364-9706559b0ca6 · outbound

This paper cites In-context Learning Distillation: Transferring Few-shot Learning Ability of Pre-trained Language Models.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes In-context Learning Distillation: Transferring Few-shot Learning Ability of Pre-trained Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:38.817872Z

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Observation 830b141c-608c-4e24-b460-41728c4a8649 · outbound

This paper cites In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:38.924089Z

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Observation aaca27e1-db15-48de-b5f3-26108e673bf0 · outbound

This paper cites Knowledge distilla- tion from language-oriented to emergent communication for multi-agent remote control.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Knowledge distilla- tion from language-oriented to emergent communication for multi-agent remote control

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:13:44.353460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0feecf44-495e-4e64-8733-1c715c94da7d · outbound

This paper cites Embodied CoT Distillation From LLM To Off-the-shelf Agents.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Embodied CoT Distillation From LLM To Off-the-shelf Agents

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:13:41.854064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2f2376da-c7ce-4ee9-97d7-a0d8e0782a53 · outbound

This paper cites OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:39.194980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54b2e3f0-b546-462f-8b93-9931aa217ecc · outbound

This paper cites AutoAgents: A Framework for Automatic Agent Generation.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes AutoAgents: A Framework for Automatic Agent Generation

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:39.304616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 777652d0-e7e8-4b7b-8870-5e34b4bd4c97 · outbound

This paper cites Long Term Memory: The Foundation of AI Self-Evolution.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Long Term Memory: The Foundation of AI Self-Evolution

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:39.441986Z

Source-reported events for the cited work

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Observation c9ca9bc0-a5c2-4787-b710-06d16fc3bc0e · outbound

This paper cites FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:39.565126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a135c201-56fb-4233-a629-916e364d4a5a · outbound

This paper cites ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:39.683134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ca0d60a-1d3a-4bef-838f-615c1377aca1 · outbound

This paper cites Clinicalagent: Clinical trial multi-agent system with large language model-based reasoning.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Clinicalagent: Clinical trial multi-agent system with large language model-based reasoning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:13:44.215254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 379f2157-a833-4a53-b1f7-e6f8344d5614 · outbound

This paper cites AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:39.962963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06fd1412-fd8d-4364-b439-17b41e1021f9 · outbound

This paper cites AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligence.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligence

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:40.022859Z

Source-reported events for the cited work

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Observation 3689c510-3d1f-456a-8e76-75e86693e517 · outbound

This paper cites Protagents: protein discovery via large language model multi-agent collaborations combining physics and machine learning.Digital Discovery, 3(7):1389–1409, 2024.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Protagents: protein discovery via large language model multi-agent collaborations combining physics and machine learning.Digital Discovery, 3(7):1389–1409, 2024

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:13:44.041533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c15b03d3-e3b3-4b99-8f34-2ddb2d552fd8 · outbound

This paper cites On Path to Multimodal Historical Reasoning: HistBench and HistAgent.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes On Path to Multimodal Historical Reasoning: HistBench and HistAgent

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:40.295752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35496410-0001-437a-a02b-6d0b998ee4c6 · outbound

This paper cites EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safety.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safety

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:40.412249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5965c5b2-182f-4eef-935a-caf105837165 · outbound

This paper cites ‘smo- lagents‘: a smol library to build great agentic systems.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes ‘smo- lagents‘: a smol library to build great agentic systems

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:40.562225Z

Source-reported events for the cited work

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Observation 7e3f7701-4150-4c28-9cef-c3607b890e87 · outbound

This paper cites Math twenty four (24 -game) dataset.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Math twenty four (24 -game) dataset

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:13:43.859421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c5ba3a17-d132-48a4-99f3-47af384cb57b · outbound

This paper cites PathVQA: 30000+ Questions for Medical Visual Question Answering.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes PathVQA: 30000+ Questions for Medical Visual Question Answering

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:40.882095Z

Source-reported events for the cited work

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Observation 21544595-8612-403b-aabd-5a6a2a78b03e · outbound

This paper cites Slake: A semantically-labeled knowledge- enhanced dataset for medical visual question answering.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes Slake: A semantically-labeled knowledge- enhanced dataset for medical visual question answering

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:40.970589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18732e9a-a776-4c55-a718-0992234bcca4 · outbound

This paper cites OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning.

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T00:13:41.081140Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation b9cdfc19-79fd-438b-b499-37108b44385d · inbound

MENTOR: Reinforcement Learning via Flexible Teacher-Optimized Rewards for Tool-Use Distillation cites this paper.

MENTOR: Reinforcement Learning via Flexible Teacher-Optimized Rewards for Tool-Use Distillation AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T08:55:58.708980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b12e3467-f880-4618-9804-96f11ab326a2 · inbound

Limits of Spatial Imagery Reasoning in Frontier LLM Models cites this paper.

Limits of Spatial Imagery Reasoning in Frontier LLM Models AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-13T19:19:52.557913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd630497-c1d1-488f-94a8-f4c66399a60c · inbound

Social Dynamics as Critical Vulnerabilities that Undermine Objective Decision-Making in LLM Collectives cites this paper.

Social Dynamics as Critical Vulnerabilities that Undermine Objective Decision-Making in LLM Collectives AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T00:00:57.105348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ff2e6df0-3fdf-4514-b7d1-39f8e5d60074 · inbound

Learning Agent Routing From Early Experience cites this paper.

Learning Agent Routing From Early Experience AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T04:35:57.749352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 60e5ff4a-dbf4-4815-96fa-c979439eada3 · inbound

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications cites this paper.

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:20:56.933868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 21ebe58b-5982-4443-af5f-bcdc8d34069d · inbound

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications cites this paper.

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-05-20T23:19:14.965828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f70fc99e-1935-41a3-957d-31160fc6c87d · inbound

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications cites this paper.

A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-06-30T23:25:07.396202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 78e615e7-2449-4ac4-aa66-e2da5269144a · inbound

SOD: Step-wise On-policy Distillation for Small Language Model Agents cites this paper.

SOD: Step-wise On-policy Distillation for Small Language Model Agents AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:40:54.398511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9b4be4b9-947e-4fa0-84f5-a8bf8541b995 · inbound

SOD: Step-wise On-policy Distillation for Small Language Model Agents cites this paper.

SOD: Step-wise On-policy Distillation for Small Language Model Agents AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T05:20:45.006003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3926dbe7-7995-4e3d-a6e7-c4548323d02d · inbound

SKILL-DISCO: Distilling and Compiling Agent Traces into Reusable Procedural Skills cites this paper.

SKILL-DISCO: Distilling and Compiling Agent Traces into Reusable Procedural Skills AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:39:50.585265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 08c2aabf-7d06-41c1-bab8-e2337eb7ef2b · inbound

AgentBrew: Lifelong Knowledge Brewing from Strong Teachers to Weak LLM Agents cites this paper.

AgentBrew: Lifelong Knowledge Brewing from Strong Teachers to Weak LLM Agents AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T19:47:37.868208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df8384d3-58dc-4826-b17d-b39bfb9a2bcf · inbound

From Trajectories to Prefixes: Reusing Teacher Trajectories via Replayed Prefixes and Online Continuation cites this paper.

From Trajectories to Prefixes: Reusing Teacher Trajectories via Replayed Prefixes and Online Continuation AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T08:56:35.330429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b31989bc-dffa-42da-a2ab-444e87f86a04 · inbound

Agent Memory Distillation: Empowering Small LLM Agents with Hierarchical Teacher Memory cites this paper.

Agent Memory Distillation: Empowering Small LLM Agents with Hierarchical Teacher Memory AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T13:41:59.147784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.