Paper Citation Record · LEDGER

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration

As of 15 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2507.05244.

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

pith.paper-citation-record.v1
2507.05244 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:36:24.222985Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T10:27:47.896922Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T09:17:48.521036Z

Reference resolution

40 of 40 outbound references displayed

verified exact0
verified fuzzy34
unresolved3
parse uncertain0
malformed identifier3
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d7ad40d9-96dd-4eea-a3b0-2f7505fab22c · outbound

This paper cites On the utility of learning about humans for human-ai coordina- tion.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration On the utility of learning about humans for human-ai coordina- tion

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:25.048179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 50de4ae7-79ec-487a-92ec-655d0f62930e · outbound

This paper cites Coordina- tion in multiagent reinforcement learning: A bayesian approach.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Coordina- tion in multiagent reinforcement learning: A bayesian approach

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:25.032919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6bc7df8b-e3b4-479f-a3f5-26e2a5248444 · outbound

This paper cites Generating diverse cooperative agents by learning incompatible policies.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Generating diverse cooperative agents by learning incompatible policies

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:25.017336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2fad4f2c-c997-4100-81cc-a901aa55b9d5 · outbound

This paper cites Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?

Reference 4

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Source-reported events for the cited work

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Observation b51113b8-a92f-4cda-850b-1a542c7426b1 · outbound

This paper cites Hidden parameter markov decision processes: A semiparamet- ric regression approach for discovering latent task parametrizations.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Hidden parameter markov decision processes: A semiparamet- ric regression approach for discovering latent task parametrizations

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:25.000918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 98a2c534-cf03-47c9-bdd9-977dc1b9b49f · outbound

This paper cites Learning with opponent- learning awareness.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Learning with opponent- learning awareness

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.984751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 48250093-7ac2-4878-a83d-b797854c968c · outbound

This paper cites Bayesian action de- coder for deep multi-agent reinforcement learning.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Bayesian action de- coder for deep multi-agent reinforcement learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.968853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d68e626d-72a8-4ece-8b48-66ab94bcbaec · outbound

This paper cites A decision-theoretic generalization of on-line learning and an application to boosting.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration A decision-theoretic generalization of on-line learning and an application to boosting

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.951777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ab49c036-64fa-437d-9ced-3efd8de13230 · outbound

This paper cites Learning policy represen- tations in multiagent systems.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Learning policy represen- tations in multiagent systems

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.937414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation de3f13c9-3661-4cfd-a33f-98ade651c521 · outbound

This paper cites Development of NASA-TLX (task load index): Results of empirical and theoretical research.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Development of NASA-TLX (task load index): Results of empirical and theoretical research

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.921389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 55fe3803-1f1d-4f66-94b8-baa25f598923 · outbound

This paper cites Opponent modeling in deep reinforcement learning.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Opponent modeling in deep reinforcement learning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.905491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 14d94194-7ca8-47e9-90a5-d790378df215 · outbound

This paper cites Fictitious self-play in extensive-form games.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Fictitious self-play in extensive-form games

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.889416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f5cc3ec5-d821-4aa7-b595-0caf8dc08425 · outbound

This paper cites Tracking the best expert.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Tracking the best expert

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.872854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 40ed6053-2e65-42bc-81a8-5dd962462ebe · outbound

This paper cites Learning to influence human behavior with offline reinforcement learning.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Learning to influence human behavior with offline reinforcement learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.856480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6e17e0d2-9fcd-4ba7-a39f-6ce71465028f · outbound

This paper cites other-play.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration other-play

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.841458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 179a62ff-ae9d-4a92-94e6-46fdba492c82 · outbound

This paper cites Human-level performance in 3d multiplayer games with population-based reinforcement learning.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Human-level performance in 3d multiplayer games with population-based reinforcement learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.823773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 45508aeb-c1ee-4b65-bab3-b138a6dc739a · outbound

This paper cites Auto-encoding variational bayes, 2013.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Auto-encoding variational bayes, 2013

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.807379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5a7e335b-8d05-4dcf-9792-6ef75b10f0a2 · outbound

This paper cites Theory of mind for multi-agent col- laboration via large language models.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Theory of mind for multi-agent col- laboration via large language models

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.790493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 558ebccd-21c0-42ab-810f-6c7cdfa581e5 · outbound

This paper cites Individualized mutual adaptation in human- agent teams.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Individualized mutual adaptation in human- agent teams

Reference 19

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Source-reported events for the cited work

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Observation f6562e60-d27e-43da-a3be-9b4152db1281 · outbound

This paper cites Theory of mind modeling in search and rescue teams.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Theory of mind modeling in search and rescue teams

Reference 20

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Source-reported events for the cited work

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Observation 75b31ece-5166-4ba9-9405-7cf1365af545 · outbound

This paper cites Learning to cooperate with humans using generative agents.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Learning to cooperate with humans using generative agents

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.775271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b2daf4fa-de2d-4e57-b7eb-3e707f41296c · outbound

This paper cites Trajectory diversity for zero-shot coordination.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Trajectory diversity for zero-shot coordination

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.760743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f84c28d1-2ae2-4f0e-9c88-6c73943467ac · outbound

This paper cites Follow-the-regularized-leader and mirror descent: Equivalence theorems and l1 regular- ization.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Follow-the-regularized-leader and mirror descent: Equivalence theorems and l1 regular- ization

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.746224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 531c507e-44de-4c02-bb1c-ad0d177e7dd5 · outbound

This paper cites Efficient model learning from joint-action demonstrations for human-robot collaborative tasks.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Efficient model learning from joint-action demonstrations for human-robot collaborative tasks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.731662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 734d94ad-cc2b-499c-bd3e-fa7cf1fcd121 · outbound

This paper cites Theory of mind as intrinsic motivation for multi-agent reinforcement learning.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Theory of mind as intrinsic motivation for multi-agent reinforcement learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.716889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d4cf384a-9f5e-4771-941e-3093c0cf830d · outbound

This paper cites Variational Autoencoders for Opponent Modeling in Multi-Agent Systems.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Variational Autoencoders for Opponent Modeling in Multi-Agent Systems

Reference 26

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Source-reported events for the cited work

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Observation 70bd011e-6787-4161-a5e6-192fea3c2cdd · outbound

This paper cites Machine theory of mind.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Machine theory of mind

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.702006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 944fb5de-82ff-49c3-b102-bc4bc540fad9 · outbound

This paper cites Modeling others using oneself in multi-agent reinforcement learning.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Modeling others using oneself in multi-agent reinforcement learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.688096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 12e3f6e0-4af5-4c42-90ff-a8e3ed6b2d33 · outbound

This paper cites Silhouettes: a graphical aid to the interpretation and validation of cluster analysis.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Silhouettes: a graphical aid to the interpretation and validation of cluster analysis

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.674024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2be3834c-432c-4355-a9de-364ef2a89842 · outbound

This paper cites an unresolved cited work.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Unresolved cited work

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8f5a923d-7840-47bc-a4b5-4c5bf9c2ffbf · outbound

This paper cites Proximal Policy Optimization Algorithms.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Proximal Policy Optimization Algorithms

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T19:36:24.179509Z

Source-reported events for the cited work

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Observation 58c93b82-b7b4-42d7-9b32-00a4813ed5b9 · outbound

This paper cites Mastering the game of go without human knowledge.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Mastering the game of go without human knowledge

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.658732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5bdeaf24-b2ab-4c2f-9c4c-1e84058f716c · outbound

This paper cites Ad hoc autonomous agent teams: Collab- oration without pre-coordination.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Ad hoc autonomous agent teams: Collab- oration without pre-coordination

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.642771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f1e50493-c5d2-4589-8e16-0279c19e6a02 · outbound

This paper cites Collaborating with humans without human data.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Collaborating with humans without human data

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.627974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b3b661e6-3de2-430d-acca-641232707e5d · outbound

This paper cites Grandmaster level in starcraft ii using multi-agent reinforcement learning.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Grandmaster level in starcraft ii using multi-agent reinforcement learning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.611804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fe483511-dff7-43e1-939d-f307e39e59b4 · outbound

This paper cites Zsc-eval: An evaluation toolkit and benchmark for multi- agent zero-shot coordination.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Zsc-eval: An evaluation toolkit and benchmark for multi- agent zero-shot coordination

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.594103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 21ec543e-6e90-47d5-803c-2bb3edb10f84 · outbound

This paper cites Learning latent representations to influence multi-agent interaction.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Learning latent representations to influence multi-agent interaction

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.577424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 047744ec-a1a6-40ad-8620-207ae8559b38 · outbound

This paper cites Coordination with humans via strategy matching.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Coordination with humans via strategy matching

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.561624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8867f33d-d984-473d-9757-057299f44912 · outbound

This paper cites Maximum entropy population-based training for zero- shot human-ai coordination.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Maximum entropy population-based training for zero- shot human-ai coordination

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.546322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e5bc498c-e2e0-409b-86a0-122cf934c042 · outbound

This paper cites Deep interactive bayesian reinforcement learning via meta-learning.

Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration Deep interactive bayesian reinforcement learning via meta-learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:36:24.529968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation 1f454dba-8356-4e33-b397-95532e1da749 · inbound

Implicit Neural Representations of Individual Behavior cites this paper.

Implicit Neural Representations of Individual Behavior Modeling Latent Partner Strategies for Adaptive Zero-Shot Human-Agent Collaboration

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-03T09:17:48.522565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.