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Paper Citation Record · LEDGER

Interactive Task Alignment as a POMDP

As of 9 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.16412.

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

pith.paper-citation-record.v1
2607.16412 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T21:04:43.450565Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

25 of 25 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fd0abe64-e5e8-4681-bd75-fb3cb426ff0d · outbound

This paper cites STaR-GATE: Teaching Language Models to Ask Clarifying Questions.

Interactive Task Alignment as a POMDP STaR-GATE: Teaching Language Models to Ask Clarifying Questions

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:39.930639Z digest=sha256:b53c5c5456a8f1475f86d041accb215aef4e5ded02666422561ee47a9dde2725

Observation bcb89a8c-f87e-4300-a280-10d76694144c · outbound

This paper cites Learning to clarify: Multi-turn conversations with action-based contrastive self-training.

Interactive Task Alignment as a POMDP Learning to clarify: Multi-turn conversations with action-based contrastive self-training

Reference 2

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:40.049417Z digest=sha256:cfead3fb0ba4220a768e29ae169045027481758dfaac698b472caa02494f8731

Observation da643ae5-0a4c-4a6f-9391-3b10b228bfcc · outbound

This paper cites Clark and Susan E.

Interactive Task Alignment as a POMDP Clark and Susan E

Reference 3

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:40.228803Z digest=sha256:53439987f1911b1ceeadbbe73cafb980ef28eb287b9d00f326221008e1235da8

Observation b2a2e3fb-131e-40a0-ba32-7f19f4c31df8 · outbound

This paper cites Bayesian Preference Elicitation with Language Models.

Interactive Task Alignment as a POMDP Bayesian Preference Elicitation with Language Models

Reference 4

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:40.393890Z digest=sha256:d9aa929a56fc30956cc7e78b34a8e1fe9739d33fe691cb0fd27347444fe5f769

Observation 1f130e03-7e73-4a6a-a894-929259c012a4 · outbound

This paper cites Teaching language models to gather information proactively.

Interactive Task Alignment as a POMDP Teaching language models to gather information proactively

Reference 5

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no resolver link, observed 2026-08-01T21:04:40.585472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:40.585472Z digest=sha256:dc41ba74ad292d7ae4a56b48e4c0472610b9c032744db3fd59761d6aefdd5761

Observation 66eb771e-676f-4306-b51e-88cd0faaf193 · outbound

This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

Interactive Task Alignment as a POMDP SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:40.721413Z digest=sha256:108918be6f06a20674dfaa06a065b5ed82f73105e2e4fe6e688ddac7043da14e

Observation b23ee6b3-f080-4188-b974-c176e85d5747 · outbound

This paper cites Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models.

Interactive Task Alignment as a POMDP Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:40.927883Z digest=sha256:8a9b882d0575eb246fa015bf2a6bfecbc77494df3ec41a567c28265309f9dacd

Observation 676e86b9-7ce0-4ef2-8c5a-2ec2da2f2314 · outbound

This paper cites DiscoverLLM: From Executing Intents to Discovering Them.

Interactive Task Alignment as a POMDP DiscoverLLM: From Executing Intents to Discovering Them

Reference 8

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:41.071741Z digest=sha256:feb10b42642ee90b4384fa831d223561e8441e3aa6ba87a3046ebfdfb2c5ceaa

Observation 8d7fc0d5-2c64-4cf0-a517-bd71ab9412e7 · outbound

This paper cites Li, Been Kim, and Zi Wang.

Interactive Task Alignment as a POMDP Li, Been Kim, and Zi Wang

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:41.272117Z digest=sha256:08e4a0f34f217b66606b3881effac321faedd8f1a9fdfe226280eade8eb19061

Observation 04c52f29-a8fd-4793-b3f7-81206694b631 · outbound

This paper cites PrefPalette: Personalized Preference Modeling with Latent Attributes.

Interactive Task Alignment as a POMDP PrefPalette: Personalized Preference Modeling with Latent Attributes

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:41.422395Z digest=sha256:0701369a8b1c0b864e6b3e02af209e4a26ac240cff9b99e99a77d9987add9ec4

Observation 287f26e7-864c-442c-9261-58cda4897824 · outbound

This paper cites Clarifymt-bench: Benchmarking and improving multi-turn clarification for conversational large language models, 2025.

Interactive Task Alignment as a POMDP Clarifymt-bench: Benchmarking and improving multi-turn clarification for conversational large language models, 2025

Reference 11

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:41.594837Z digest=sha256:033b9fa8f0883fa60b0c4d26b0d7ba1dd341dfe79b122035d3100d1f5d41a90c

Observation df343f97-5744-400d-965b-a4792ae1e234 · outbound

This paper cites Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces.

Interactive Task Alignment as a POMDP Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces

Reference 12

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:41.711576Z digest=sha256:3975b7fcea8119142a03fe25562d66a15d4581c27d7257dad4390c4b3084f8f2

Observation 6b741c6b-4cb9-4c73-9df3-4f80c39caa5f · outbound

This paper cites Asking clarifying questions for preference elicitation with large language models, 2025.

Interactive Task Alignment as a POMDP Asking clarifying questions for preference elicitation with large language models, 2025

Reference 13

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:41.835327Z digest=sha256:3da98ffe1731dcb225ac3dc1e7220af926b848b71c5ef570bda04c56b4236a65

Observation d321a8f4-bf75-42a6-bea5-9f53e6170a9d · outbound

This paper cites GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks.

Interactive Task Alignment as a POMDP GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks

Reference 14

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no resolver link, observed 2026-08-01T21:04:41.955454Z

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source=arxiv_source observed=2026-08-01T21:04:41.955454Z digest=sha256:7b4e4890771bcca35a662949f8b943c55466bf53aae2a5176cd4310e31b0db67

Observation e2f2f790-482f-4e0c-a137-01a2713b2c41 · outbound

This paper cites Tell me more! towards implicit user intention understanding of language model driven agents.

Interactive Task Alignment as a POMDP Tell me more! towards implicit user intention understanding of language model driven agents

Reference 15

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source=arxiv_source observed=2026-08-01T21:04:42.138369Z digest=sha256:7bf80699c785bae83573216be114b2a70fb0b857a1fe2adf2ff6fce19d7bf448

Observation 63646e63-58b1-4a51-8905-57c45cf2ca4d · outbound

This paper cites Ambig-swe: Interactive agents to overcome underspecificity in software engineering, 2026.

Interactive Task Alignment as a POMDP Ambig-swe: Interactive agents to overcome underspecificity in software engineering, 2026

Reference 16

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:42.237599Z digest=sha256:98082bd92b534ed5d041095e75245fc925eb121b934de7c44b8dd941e7d1bd2d

Observation c31ec5f3-eb14-4508-9995-269e8aed0c6f · outbound

This paper cites RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning.

Interactive Task Alignment as a POMDP RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning

Reference 17

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source=arxiv_source observed=2026-08-01T21:04:42.348283Z digest=sha256:58d31adefb705886ef9206a1abca98bfc95224ad99154eeef8e0abeaf6df7c4a

Observation 4078935f-6ffb-4ca8-b9d4-349616496b8f · outbound

This paper cites Position: Humans are missing from ai coding agent research, 2025 b.

Interactive Task Alignment as a POMDP Position: Humans are missing from ai coding agent research, 2025 b

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:42.470253Z digest=sha256:7742bf83dc5bf0e6b90425fe0fb76fb1852b0acafd12eca3f49210f402518394

Observation 39f5dc40-a92c-4153-8e70-ba5d1b8d2955 · outbound

This paper cites BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents.

Interactive Task Alignment as a POMDP BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents

Reference 19

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:42.629972Z digest=sha256:b92334ce5cff66b1f3214e45da44a8a48b772519c6315e90add452625d86b77b

Observation 9f7977a0-6d2e-478c-b56d-f799f1e3eb08 · outbound

This paper cites CollabLLM: From Passive Responders to Active Collaborators.

Interactive Task Alignment as a POMDP CollabLLM: From Passive Responders to Active Collaborators

Reference 20

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source=arxiv_source observed=2026-08-01T21:04:42.772581Z digest=sha256:879dc241b525ca49301d7f17aa24e2c53ce47403cd00431d32ce51e98633d818

Observation 1d28acc1-5856-433a-ace0-009f5171147a · outbound

This paper cites Aligning LLMs with Individual Preferences via Interaction.

Interactive Task Alignment as a POMDP Aligning LLMs with Individual Preferences via Interaction

Reference 21

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:42.889953Z digest=sha256:8ebb6d5dfcc29d23b6de031ccb7af321aae9355166985b4938caabb03489ecce

Observation 0f0c53fd-876b-4b31-9d5c-559489edbf5f · outbound

This paper cites WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents.

Interactive Task Alignment as a POMDP WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents

Reference 22

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no resolver link, observed 2026-08-01T21:04:43.009747Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:43.009747Z digest=sha256:2472288ca86e9efc439acc6759e0c2f5c83d19d35913f08899cb6a81557524a9

Observation 1e50d021-a4c7-490a-9feb-3c25d658de7c · outbound

This paper cites Modeling Future Conversation Turns to Teach LLMs to Ask Clarifying Questions.

Interactive Task Alignment as a POMDP Modeling Future Conversation Turns to Teach LLMs to Ask Clarifying Questions

Reference 23

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source=arxiv_source observed=2026-08-01T21:04:43.137464Z digest=sha256:a37a8b1a5d04475ab322598e95f9d7b6bb6e80df5116064307651df8bf62f17f

Observation 7ff770c2-ca76-46d0-b438-d70203f62e7c · outbound

This paper cites Clarify when necessary: Resolving ambiguity through interaction with lms.

Interactive Task Alignment as a POMDP Clarify when necessary: Resolving ambiguity through interaction with lms

Reference 24

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:43.303549Z digest=sha256:9578b4f448777680d0026c30ed9ca9849d8c9b096a99b33a34e739635df2b833

Observation 24566c9c-ae0b-4fb0-8e9b-0b906f430cad · outbound

This paper cites Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs.

Interactive Task Alignment as a POMDP Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs

Reference 25

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:04:43.450565Z digest=sha256:310ee7226bf16fea3f0ed8417d92ff4014fe797ad4f18293bbd73d4adc4269ec

Pith citing papers

No inbound Pith citation observations are available.