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Paper Citation Record · LEDGER

Provably Optimal Learning Algorithms for Assistance Games

As of 19 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2607.08012.

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

pith.paper-citation-record.v1
2607.08012 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T13:46:04.338440Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

58 of 58 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bf57c6c5-f56e-46dc-baf0-ef98ee61337c · outbound

This paper cites Improved differentially private and lazy online convex optimization: Lower regret without smoothness requirements.

Provably Optimal Learning Algorithms for Assistance Games Improved differentially private and lazy online convex optimization: Lower regret without smoothness requirements

Reference 1

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Observation 4efe94e3-32e7-4406-816e-1f67572b0393 · outbound

This paper cites Online learning over a finite action set with limited switching.

Provably Optimal Learning Algorithms for Assistance Games Online learning over a finite action set with limited switching

Reference 2

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Observation 10e15044-adc5-483f-8311-5ee81c7ab7ea · outbound

This paper cites Human expertise in algorithmic prediction.

Provably Optimal Learning Algorithms for Assistance Games Human expertise in algorithmic prediction

Reference 3

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This paper cites Online learning for adversaries with memory: price of past mistakes.

Provably Optimal Learning Algorithms for Assistance Games Online learning for adversaries with memory: price of past mistakes

Reference 4

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Observation e5b3c055-33ae-4141-91ba-5b17ef455173 · outbound

This paper cites The allocation of decision authority to human and artificial intelligence.

Provably Optimal Learning Algorithms for Assistance Games The allocation of decision authority to human and artificial intelligence

Reference 5

Resolution
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 865282b5-1446-4030-943f-0a29b1490356 · outbound

This paper cites Does the whole exceed its parts? the effect of ai explanations on complementary team performance.

Provably Optimal Learning Algorithms for Assistance Games Does the whole exceed its parts? the effect of ai explanations on complementary team performance

Reference 6

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c7eba8c3-5824-4195-8fa4-0e3f960b4793 · outbound

This paper cites Is learning in games good for the learners? Advances in Neural Information Processing Systems, 36, 2024.

Provably Optimal Learning Algorithms for Assistance Games Is learning in games good for the learners? Advances in Neural Information Processing Systems, 36, 2024

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e3573cb1-5c05-4a81-bf38-abc99cfd00b5 · outbound

This paper cites Mirror descent meets fixed share (and feels no regret).

Provably Optimal Learning Algorithms for Assistance Games Mirror descent meets fixed share (and feels no regret)

Reference 8

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9d67f9cc-edb3-46c8-943a-6a08622e5022 · outbound

This paper cites Emergent communication at scale.

Provably Optimal Learning Algorithms for Assistance Games Emergent communication at scale

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5a483dd5-3abc-4e0e-8844-499bde85652d · outbound

This paper cites Dependent randomized rounding via exchange properties of combinatorial structures.

Provably Optimal Learning Algorithms for Assistance Games Dependent randomized rounding via exchange properties of combinatorial structures

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d9ab3098-1349-4975-a61e-aec5c8ab5b73 · outbound

This paper cites On the np-completeness of finding an optimal strategy in games with common payoffs.

Provably Optimal Learning Algorithms for Assistance Games On the np-completeness of finding an optimal strategy in games with common payoffs

Reference 11

Resolution
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Source-reported events for the cited work

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Observation d8aa3727-bcf9-485b-bd4c-d53e80cec3a2 · outbound

This paper cites Collaborative prediction: Tractable information aggregation via agreement.

Provably Optimal Learning Algorithms for Assistance Games Collaborative prediction: Tractable information aggregation via agreement

Reference 12

Resolution
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Source-reported events for the cited work

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Observation 860d8b59-595d-450a-bfba-4416748caf9c · outbound

This paper cites Computing the optimal strategy to commit to.

Provably Optimal Learning Algorithms for Assistance Games Computing the optimal strategy to commit to

Reference 13

Resolution
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Source-reported events for the cited work

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Observation 0f8fd976-3091-47ec-82d6-94b2dfb9d8fc · outbound

This paper cites Strongly adaptive online learning.

Provably Optimal Learning Algorithms for Assistance Games Strongly adaptive online learning

Reference 14

Resolution
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Source-reported events for the cited work

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Observation 32d0adf9-af4d-415f-b910-54b4e8eb75c4 · outbound

This paper cites Human-algorithm collaboration: Achieving complementarity and avoiding unfairness.

Provably Optimal Learning Algorithms for Assistance Games Human-algorithm collaboration: Achieving complementarity and avoiding unfairness

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 93d615d2-0583-4b74-b234-3c1db4196fc2 · outbound

This paper cites A threshold of ln n for approximating set cover.

Provably Optimal Learning Algorithms for Assistance Games A threshold of ln n for approximating set cover

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9ed5cea4-32b1-43d4-a32e-3bb98e87b57a · outbound

This paper cites A decision-theoretic model of assistance.

Provably Optimal Learning Algorithms for Assistance Games A decision-theoretic model of assistance

Reference 17

Resolution
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Observation 5bf1adff-5cc1-4763-9807-51157cea4c68 · outbound

This paper cites Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks.

Provably Optimal Learning Algorithms for Assistance Games Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks

Reference 18

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Source-reported events for the cited work

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Observation 308c8182-b1d1-4c18-9aa1-7dcf6842f4e5 · outbound

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Provably Optimal Learning Algorithms for Assistance Games Interpretation of optimal signals

Reference 19

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Source-reported events for the cited work

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Observation 8f29d5c4-98d1-45ff-9501-b1e8551fd92b · outbound

This paper cites Signal to act: Game theory in pragmatics.

Provably Optimal Learning Algorithms for Assistance Games Signal to act: Game theory in pragmatics

Reference 20

Resolution
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Source-reported events for the cited work

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Observation 282c5dee-bb4e-4c07-b83c-4de7e27760f1 · outbound

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Provably Optimal Learning Algorithms for Assistance Games Nash and correlated equilibria: Some complexity considerations

Reference 21

Resolution
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Source-reported events for the cited work

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Provably Optimal Learning Algorithms for Assistance Games The principles and limits of algorithm-in-the-loop decision making

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6baaf041-e370-4bed-a78b-97ee8d484eff · outbound

This paper cites Designing algorithmic delegates: The role of indistinguishability in human-ai handoff.

Provably Optimal Learning Algorithms for Assistance Games Designing algorithmic delegates: The role of indistinguishability in human-ai handoff

Reference 23

Resolution
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Source-reported events for the cited work

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Observation 676bf65e-adb6-470e-895b-9921e1a265de · outbound

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Provably Optimal Learning Algorithms for Assistance Games Cooperative inverse reinforcement learning

Reference 24

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Source-reported events for the cited work

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Observation 76b66119-62cf-4cb0-bbdb-5b01a6bc7a23 · outbound

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Provably Optimal Learning Algorithms for Assistance Games The off-switch game

Reference 25

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8f2e8279-f852-4b7d-95b7-10514d372c74 · outbound

This paper cites Emergence of language with multi-agent games: Learning to communicate with sequences of symbols.

Provably Optimal Learning Algorithms for Assistance Games Emergence of language with multi-agent games: Learning to communicate with sequences of symbols

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

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Provably Optimal Learning Algorithms for Assistance Games Adaptive algorithms for online decision problems

Reference 27

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Provably Optimal Learning Algorithms for Assistance Games Tracking the best expert

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Provably Optimal Learning Algorithms for Assistance Games Team decision theory and information structures in optimal control problems--part i

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Provably Optimal Learning Algorithms for Assistance Games Regularized Conventions: Equilibrium Computation as a Model of Pragmatic Reasoning

Reference 30

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a614084e-3d01-408c-8708-2ab4997f434b · outbound

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Provably Optimal Learning Algorithms for Assistance Games Game dynamics connects semantics and pragmatics

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b4415652-6186-4394-8402-973e1c4b4c17 · outbound

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Provably Optimal Learning Algorithms for Assistance Games Game theory in semantics and pragmatics

Reference 32

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4f071f21-d9c1-48e7-85a1-9659846c78c5 · outbound

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Provably Optimal Learning Algorithms for Assistance Games Online submodular welfare maximization: Greedy is optimal

Reference 33

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 95e0472c-2ee3-4045-9f89-f6d6784763e3 · outbound

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Provably Optimal Learning Algorithms for Assistance Games Emergent communication under varying sizes and connectivities

Reference 34

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Provably Optimal Learning Algorithms for Assistance Games Natural language from artificial life

Reference 35

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 03a877a7-6d71-47b1-bbba-04dd0bacd061 · outbound

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Provably Optimal Learning Algorithms for Assistance Games Iterated learning and the evolution of language

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.931601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:1eb64832c4c8c1d801f4ddaadf2dad3e45c3cb46fab77548164b88594d55b67f

Observation 63fe05d7-971c-4a90-84f2-4cebe6dc99b6 · outbound

This paper cites Assistancezero: Scalably solving assistance games.

Provably Optimal Learning Algorithms for Assistance Games Assistancezero: Scalably solving assistance games

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.960645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:3e931a67261bf54b0703383465ecdb351d29b5fc0b7abf1ec40e23d4906481c8

Observation eeed42ea-9491-41e7-bd7c-528e71fe7a3d · outbound

This paper cites Emergent Multi-Agent Communication in the Deep Learning Era.

Provably Optimal Learning Algorithms for Assistance Games Emergent Multi-Agent Communication in the Deep Learning Era

Reference 38

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T13:47:05.758235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:7ee390bd8c5184c8f3a731f90e5baff3516953e378d90ddfc400298fead50ff4

Observation e49d094d-3a26-4bab-af74-441d52f5537d · outbound

This paper cites Multi-Agent Cooperation and the Emergence of (Natural) Language.

Provably Optimal Learning Algorithms for Assistance Games Multi-Agent Cooperation and the Emergence of (Natural) Language

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.760816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:7bf6fad19f7917461e811969dd64728fe5051d8bbe7f982e3a557bbf1e32798a

Observation 1b46fa3a-c47c-4048-80bd-d3ef919f605f · outbound

This paper cites Learning and approximating the optimal strategy to commit to.

Provably Optimal Learning Algorithms for Assistance Games Learning and approximating the optimal strategy to commit to

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.956196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:10f455c66fd69e66031757cf935d84072a19ccf2e218a10509d522224b1ccb8e

Observation a98108da-74fd-43f8-954c-90aa50674464 · outbound

This paper cites Ease-of-teaching and language structure from emergent communication.

Provably Optimal Learning Algorithms for Assistance Games Ease-of-teaching and language structure from emergent communication

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.901456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:f715996cef7e0ac77d20c609bec9cbf4ceca1156adf27ecc1bc09935ba703d69

Observation 54c138e6-84ad-412d-afce-637aa1cc1d26 · outbound

This paper cites The geometry of logconcave functions and sampling algorithms.

Provably Optimal Learning Algorithms for Assistance Games The geometry of logconcave functions and sampling algorithms

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.866640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:88f3e494207d350a9b98be13c723e8af6b787c17d9fb7a03717bf742af247bba

Observation 267b4bde-0474-41db-8f07-ee673a267b12 · outbound

This paper cites Decentralized stochastic control.

Provably Optimal Learning Algorithms for Assistance Games Decentralized stochastic control

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.946719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:43c64ba8098f5cecd82f59a750411ba5bd078316fa9719211038976f59f23d65

Observation 12a314d0-525d-4818-971a-7cedcc6b87bf · outbound

This paper cites An efficient, generalized bellman update for cooperative inverse reinforcement learning.

Provably Optimal Learning Algorithms for Assistance Games An efficient, generalized bellman update for cooperative inverse reinforcement learning

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.896770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:6596510daac0cfc816968d60d53ad15e810d9c59134da793a4fa89f60889ad72

Observation 3acaf064-315f-4046-9626-eac18b84e49a · outbound

This paper cites On team decision problems with nonclassical information structures.

Provably Optimal Learning Algorithms for Assistance Games On team decision problems with nonclassical information structures

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.888262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:64b0881c1609572f271075b98329ada67caab35a4ac1ce45fffcb41c2be52b01

Observation 3bc154b7-f88d-4e30-ae10-bb4020610fae · outbound

This paper cites Decentralized stochastic control with partial history sharing: A common information approach.

Provably Optimal Learning Algorithms for Assistance Games Decentralized stochastic control with partial history sharing: A common information approach

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.890167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:6a251a2c713e4911a8b983738dfe6f2acdf6f8fbf05cb784b655a85e955f6339

Observation af7ee05b-0f85-42ba-b70d-82dc52d3a22d · outbound

This paper cites Learning optimal strategies to commit to.

Provably Optimal Learning Algorithms for Assistance Games Learning optimal strategies to commit to

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.937170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:8e8595ca32dcec1c86b5082f345d9b8ec35d5c2bdb1c2c28b3cb56dd992f0bc5

Observation 7069e25b-2041-407d-b701-7afee210a515 · outbound

This paper cites Team decision problems.

Provably Optimal Learning Algorithms for Assistance Games Team decision problems

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.914067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:71dafd2c6a75769d3bd7044195a243444c9cda00719af61b530739b3054f2a3c

Observation 9be6ac91-83e7-4e64-8acd-97a7266c81ba · outbound

This paper cites Enhance the compositionality of emergent language by iterated learning.

Provably Optimal Learning Algorithms for Assistance Games Enhance the compositionality of emergent language by iterated learning

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.925855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:fe27b66fac1287c2d7a4ced82c5cb2b0cbbed104b7be209913bda2261a06c099

Observation 2cd6b146-894b-4690-8cff-0593b4eb34fc · outbound

This paper cites "LazImpa": Lazy and Impatient neural agents learn to communicate efficiently.

Provably Optimal Learning Algorithms for Assistance Games "LazImpa": Lazy and Impatient neural agents learn to communicate efficiently

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.757416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:546f337a87fba641dd56e083480d6ca5cc4a5894caa23de2d55de9ba12e5b493

Observation 2777f177-e6a3-4428-858e-bf6239ac515d · outbound

This paper cites Online submodular maximization via online convex optimization.

Provably Optimal Learning Algorithms for Assistance Games Online submodular maximization via online convex optimization

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.924128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:cd0b1dd468a3ea59f4b00b2e565958e2e68da70b2e3b46e6b1fcfc1a542b8980

Observation b2c7ea86-43b5-4c73-a428-585a25a25268 · outbound

This paper cites Benefits of assistance over reward learning, 2020.

Provably Optimal Learning Algorithms for Assistance Games Benefits of assistance over reward learning, 2020

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.908577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:30e03311969dc8808c5b58efc3b1c92990b7b242acfae169a7c5275c0bf62cb9

Observation 7c36ff80-d220-462a-8122-cfb2050fe256 · outbound

This paper cites Online learning and online convex optimization.

Provably Optimal Learning Algorithms for Assistance Games Online learning and online convex optimization

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.935149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:832536dedd70c6115ba5ad1f90933ab102c5aeaf111b9ea5fa3628b392aa8956

Observation 6599fcea-469f-4e19-a13c-4ce0fa6fb1e5 · outbound

This paper cites Lazy oco: Online convex optimization on a switching budget.

Provably Optimal Learning Algorithms for Assistance Games Lazy oco: Online convex optimization on a switching budget

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.899435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:61105daa0866556847ec336272b17cc5afa0aa93b8e4262a49955b3e97527bac

Observation d0307b8b-1f4e-48a6-b5b9-01fc6804edca · outbound

This paper cites Bayesian modeling of human--ai complementarity.

Provably Optimal Learning Algorithms for Assistance Games Bayesian modeling of human--ai complementarity

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.938812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:5b2087053fefbcbe88db0dfd9921b8a4ab412730db8fa1591448aed2980aede3

Observation 8cf58629-1e69-4522-b742-a48d4e569a35 · outbound

This paper cites Nash equilibria for an evolutionary language game.

Provably Optimal Learning Algorithms for Assistance Games Nash equilibria for an evolutionary language game

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.976875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:0001d178dcc2635b81eac8cb00f82e47fd1b076e420a5fc1766dd7cb2643141a

Observation fd09f9c0-6241-469a-bd9e-63219cce8e7b · outbound

This paper cites Learning to Complement Humans.

Provably Optimal Learning Algorithms for Assistance Games Learning to Complement Humans

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.754960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:6350403a86e41adae03932f2d10c3e058b0699acbec86b5fc94a6a3e271107f8

Observation 6768246d-b293-4de1-a3f7-1c3cfd14ff97 · outbound

This paper cites Who leads and who follows in strategic classification? Advances in Neural Information Processing Systems, 34: 0 15257--15269, 2021.

Provably Optimal Learning Algorithms for Assistance Games Who leads and who follows in strategic classification? Advances in Neural Information Processing Systems, 34: 0 15257--15269, 2021

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.934595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:6c27d7db5c557aaa3bd74c233a6b8ade4f6bd8caef15eac1f8eb0184fd8502da

Pith citing papers

No inbound Pith citation observations are available.