Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:35:37.055249Z
Paper Citation Record · LEDGER
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning
As of 21 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2506.23793.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
54 of 54 outbound references displayed
- verified exact0
- verified fuzzy45
- unresolved9
- parse uncertain0
- malformed identifier0
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation dd1aa3ae-04b9-4a14-940c-a6a63d5ed1ce · outbound
This paper cites Lifelong multi-agent path finding in large-scale warehouses,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Lifelong multi-agent path finding in large-scale warehouses,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.924230Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c9517f9b-c180-45f1-b9a1-19dbcfa9671c · outbound
This paper cites Intersection coordination with priority-based search for autonomous vehicles,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Intersection coordination with priority-based search for autonomous vehicles,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.907925Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation dd09f6f7-68b0-4023-974f-679332f6fe28 · outbound
This paper cites Multi-agent pathfinding: Definitions, variants, and benchmarks,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Multi-agent pathfinding: Definitions, variants, and benchmarks,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.891062Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 74a29688-5cc0-411e-8cff-2fc398f23c9e · outbound
This paper cites Multi-agent path finding with kinematic constraints.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Multi-agent path finding with kinematic constraints
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.876264Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6b4e0237-a65e-4959-a0b3-692c861e3b8e · outbound
This paper cites Lifelong path planning with kinematic constraints for multi-agent pickup and delivery,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Lifelong path planning with kinematic constraints for multi-agent pickup and delivery,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.860182Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation dfcf9b5e-c1d7-434d-9c80-a871a1e0b04a · outbound
This paper cites Prioritized multi- agent path finding for differential drive robots,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Prioritized multi- agent path finding for differential drive robots,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.844635Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 69500802-7848-440b-aeca-c2e38c1bc105 · outbound
This paper cites Finding optimal solutions to cooperative pathfinding problems,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Finding optimal solutions to cooperative pathfinding problems,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.829675Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 22aee36e-0e67-427e-ac24-b4e5cdb94fe1 · outbound
This paper cites Conflict-based search for optimal multi-agent pathfinding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Conflict-based search for optimal multi-agent pathfinding,
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:35:36.162983Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7be0efe0-df7a-4076-8f2b-c639b71e2881 · outbound
This paper cites M*: A complete multirobot path planning algorithm with performance bounds,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning M*: A complete multirobot path planning algorithm with performance bounds,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.804391Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 7cad0169-906d-402d-a316-f7eb9e944248 · outbound
This paper cites Efficient sat approach to multi-agent path finding under the sum of costs objec- tive,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Efficient sat approach to multi-agent path finding under the sum of costs objec- tive,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.788053Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 71986a9f-b3ad-41d5-b632-a04c88613673 · outbound
This paper cites Priority inheritance with backtracking for iterative multi-agent path finding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Priority inheritance with backtracking for iterative multi-agent path finding,
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:35:36.360084Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 05f9de3f-0fbb-4b86-bb98-4044f62ad7ce · outbound
This paper cites Lacam: Search-based algorithm for quick multi-agent pathfinding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Lacam: Search-based algorithm for quick multi-agent pathfinding,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.758995Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0deaa79c-e118-4c54-8a33-2572edd8bb48 · outbound
This paper cites Mapf- lns2: Fast repairing for multi-agent path finding via large neighbor- hood search,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Mapf- lns2: Fast repairing for multi-agent path finding via large neighbor- hood search,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.742620Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 14eced16-b9fd-4eab-bfad-7897be68721f · outbound
This paper cites An optimization variant of multi-robot path planning is intractable,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning An optimization variant of multi-robot path planning is intractable,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.725356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 4df54157-e9e9-40ab-8bc7-7e2aee4360ae · outbound
This paper cites Mapper: Multi-agent path planning with evolutionary reinforcement learning in mixed dynamic environments,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Mapper: Multi-agent path planning with evolutionary reinforcement learning in mixed dynamic environments,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.710774Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6861167c-84eb-4f40-9bb9-f8338981f494 · outbound
This paper cites Message-aware graph attention networks for large-scale multi-robot path planning,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Message-aware graph attention networks for large-scale multi-robot path planning,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.696492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ed2b60aa-c3a4-4464-8dbc-14711689e6fe · outbound
This paper cites Scrimp: Scalable communication for reinforcement-and imitation-learning-based multi- agent pathfinding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Scrimp: Scalable communication for reinforcement-and imitation-learning-based multi- agent pathfinding,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.681717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c81b304f-b780-4af8-ba06-2a815f7796ac · outbound
This paper cites Distributed heuristic multi-agent path finding with communication,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Distributed heuristic multi-agent path finding with communication,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.666510Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f0d1302e-cd4c-4e2e-9eab-c3324ee933f3 · outbound
This paper cites Learning selective communication for multi-agent path finding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Learning selective communication for multi-agent path finding,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.650608Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 3db4e1f0-2577-4c17-b508-38eadf3dfa9f · outbound
This paper cites Ensembling prioritized hybrid policies for multi-agent pathfinding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Ensembling prioritized hybrid policies for multi-agent pathfinding,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.635184Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation cd03b688-cade-4f73-87ff-945393caf32f · outbound
This paper cites Learn to follow: Decentralized lifelong multi-agent pathfinding via planning and learning,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Learn to follow: Decentralized lifelong multi-agent pathfinding via planning and learning,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.618994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation a6c65baa-0279-48dd-a348-931cf7132bdf · outbound
This paper cites When to switch: planning and learning for partially observable multi-agent pathfinding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning When to switch: planning and learning for partially observable multi-agent pathfinding,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.602922Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 3a8df2ce-2328-4399-b1ba-e6915f2ada4d · outbound
This paper cites A comprehensive review on lever- aging machine learning for multi-agent path finding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning A comprehensive review on lever- aging machine learning for multi-agent path finding,
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.589011Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 75dee056-2301-4120-b162-7bfe4db7a7c2 · outbound
This paper cites MAPF- GPT: Imitation learning for multi-agent pathfinding at scale,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning MAPF- GPT: Imitation learning for multi-agent pathfinding at scale,
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.574323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9140094b-5ed1-43b5-9121-7bcb4f14c43b · outbound
This paper cites Multi-agent imitation learning: Value is easy, regret is hard,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Multi-agent imitation learning: Value is easy, regret is hard,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.558362Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 77c97a48-4ee0-4b0e-ba08-54237a3d14c2 · outbound
This paper cites Learning multi-agent behaviors from distributed and streaming demonstrations,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Learning multi-agent behaviors from distributed and streaming demonstrations,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.544293Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b81ad8b0-f8b1-4396-9f30-11e429c798f6 · outbound
This paper cites Bayesian multi- type mean field multi-agent imitation learning,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Bayesian multi- type mean field multi-agent imitation learning,
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.529745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 252a0fcf-2a5a-471a-8791-2f8fcaf96539 · outbound
This paper cites Multi-agent generative adversarial imitation learning,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Multi-agent generative adversarial imitation learning,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.515200Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 4d2b0807-71f8-4ade-9152-f3bf26c214ec · outbound
This paper cites Gailpg: Multi-agent policy gradient with generative adversarial imitation learning,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Gailpg: Multi-agent policy gradient with generative adversarial imitation learning,
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.498345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0fa55020-88f7-48f3-9bcf-d3a719779759 · outbound
This paper cites Multi-agent imitation learning with copulas,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Multi-agent imitation learning with copulas,
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.484292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation e06f86cd-ed2f-4af5-a06a-90b10e6e3571 · outbound
This paper cites Conditional imitation learning for multi-agent games,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Conditional imitation learning for multi-agent games,
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.469667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 61869932-80c2-47e6-b980-07c67b5d4d98 · outbound
This paper cites Coordinated multi-agent imitation learning,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Coordinated multi-agent imitation learning,
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.455344Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 2e985abf-bcce-4a08-8cd5-47ae90c6edcf · outbound
This paper cites Offline pre-trained multi-agent decision transformer,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Offline pre-trained multi-agent decision transformer,
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.441976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ea98309a-248b-403b-bc87-06defd8637a5 · outbound
This paper cites Mastering the game of go with deep neural networks and tree search,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Mastering the game of go with deep neural networks and tree search,
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.427935Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation e68483bf-4547-4d7c-9bd8-c662b61ac533 · outbound
This paper cites Amortized planning with large-scale transformers: A case study on chess,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Amortized planning with large-scale transformers: A case study on chess,
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.412991Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 089c339c-e07f-4aa6-939d-c3f21a229b57 · outbound
This paper cites On the Opportunities and Risks of Foundation Models.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning On the Opportunities and Risks of Foundation Models
Reference 36
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 87235990-9198-4b19-b7ab-7f4b8e95b113 · outbound
This paper cites Foundation Models for Decision Making: Problems, Methods, and Opportunities.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Foundation Models for Decision Making: Problems, Methods, and Opportunities
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:35:36.966715Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8bcc3cd7-fd4f-4824-98be-be376f3558d6 · outbound
This paper cites Foundation models in robotics: Applications, challenges, and the future,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Foundation models in robotics: Applications, challenges, and the future,
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.398082Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 84f176d6-a7e4-4f06-9a22-07103d6c3d9f · outbound
This paper cites Octo: An Open-Source Generalist Robot Policy.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Octo: An Open-Source Generalist Robot Policy
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:35:36.976921Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b5c77707-b835-4d5f-8a4b-42ce8a51c237 · outbound
This paper cites OpenVLA: An open-source vision-language-action model,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning OpenVLA: An open-source vision-language-action model,
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.382896Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation e068fdce-c98b-4c47-a94d-173a3eda9c5b · outbound
This paper cites Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:35:36.988410Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e55d298-f30b-4ede-a024-82d5164b1738 · outbound
This paper cites Work Smarter Not Harder: Simple Imitation Learning with CS-PIBT Outperforms Large Scale Imitation Learning for MAPF.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Work Smarter Not Harder: Simple Imitation Learning with CS-PIBT Outperforms Large Scale Imitation Learning for MAPF
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:35:36.993267Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b1f37afb-d1f8-4727-890b-e112b46699e6 · outbound
This paper cites Multi-agent systems and foundation models enable autonomous supply chains: Opportunities and challenges,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Multi-agent systems and foundation models enable autonomous supply chains: Opportunities and challenges,
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.368331Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 257beee2-a2ef-4c33-a438-28c189dbdb53 · outbound
This paper cites Fine-tuning multi- modal transformer models for generating actions in virtual and real environments,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Fine-tuning multi- modal transformer models for generating actions in virtual and real environments,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.353328Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 53b0381c-9c08-4585-ab07-47aedf04d3e2 · outbound
This paper cites Archer: Training language model agents via hierarchical multi-turn rl,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Archer: Training language model agents via hierarchical multi-turn rl,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.337974Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 52dacca2-6c6c-4852-bd1f-ca629c180a90 · outbound
This paper cites Fine-tuning large vision-language models as decision-making agents via reinforcement learning,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Fine-tuning large vision-language models as decision-making agents via reinforcement learning,
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.321889Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6668de8d-7714-4d2b-9d19-b7653c5757b1 · outbound
This paper cites Robot Utility Models: General Policies for Zero-Shot Deployment in New Environments.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Robot Utility Models: General Policies for Zero-Shot Deployment in New Environments
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:35:37.017677Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c07d7e21-98a9-47fc-b8e9-6cff29650f3c · outbound
This paper cites The in- creasing cost tree search for optimal multi-agent pathfinding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning The in- creasing cost tree search for optimal multi-agent pathfinding,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.304472Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ecf40a58-b143-4e17-82a7-3fa13ea3e8be · outbound
This paper cites Searching with consistent prioritization for multi-agent path finding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Searching with consistent prioritization for multi-agent path finding,
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.288647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 610e4bde-3704-49a1-a000-973732edc67f · outbound
This paper cites Primal: Pathfinding via reinforcement and imitation multi-agent learning,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Primal: Pathfinding via reinforcement and imitation multi-agent learning,
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.270571Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 71b97b49-e319-46af-814a-b7ac7726cf9e · outbound
This paper cites Amortized planning with large-scale transformers: A case study on chess,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Amortized planning with large-scale transformers: A case study on chess,
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.254446Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ba85efd0-0d1a-49ae-836c-821e8081a0a7 · outbound
This paper cites Engineering lacam*: Towards real-time, large-scale, and near-optimal multi-agent pathfinding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Engineering lacam*: Towards real-time, large-scale, and near-optimal multi-agent pathfinding,
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.238925Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation fa5cad76-a3c9-4bc5-8e35-729b1bc6b356 · outbound
This paper cites A reduction of imitation learning and structured prediction to no-regret online learning,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning A reduction of imitation learning and structured prediction to no-regret online learning,
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:35:37.049332Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1127eaa4-b4d8-41fb-b294-ec2dd505cba9 · outbound
This paper cites Pogema: A benchmark platform for cooperative multi-agent pathfinding,.
Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Pogema: A benchmark platform for cooperative multi-agent pathfinding,
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T21:35:37.210295Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Pith citing papers
No inbound Pith citation observations are available.