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Paper Citation Record · LEDGER

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning

As of 2 August 2026, this Paper Citation Record lists 100 of 112 outbound references and 0 inbound Pith citation observations for arXiv:2607.18060.

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

pith.paper-citation-record.v1
2607.18060 v2

Coverage vector

measured 100 of 112 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T16:19:09.540151Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-01T06:32:01.292127+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

100 of 112 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved100
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 50c05fc3-baf6-4854-a2ea-14ae29fb3a2b · outbound

This paper cites Qwen3-VL Technical Report.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Qwen3-VL Technical Report

Reference 1

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source=arxiv_source observed=2026-08-01T16:19:08.878687Z digest=sha256:b6aae02ebb711579e7344fa925d6d4c38452a4cd7e3cdd2c6a79c1ff412480bc

Observation 58a5ba73-cbdd-4d4b-8f54-3c2b054e3550 · outbound

This paper cites PDDLStream : Integrating symbolic planners and blackbox samplers via optimistic adaptive planning.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning PDDLStream : Integrating symbolic planners and blackbox samplers via optimistic adaptive planning

Reference 2

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source=arxiv_source observed=2026-08-01T16:19:08.884664Z digest=sha256:f88270e3ef7391a372b1880b8d1d4be4c4eba0e1c8a32514c22c449fb614610b

Observation f662a881-d664-4f67-810b-d859cafff288 · outbound

This paper cites From Pixels to Predicates: Learning Symbolic World Models via Pretrained Vision-Language Models , journal=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning From Pixels to Predicates: Learning Symbolic World Models via Pretrained Vision-Language Models , journal=

Reference 3

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source=arxiv_source observed=2026-08-01T16:19:08.890026Z digest=sha256:9c5829f19f664eb4e75ae752e4c66b5e8279da946aba7158fec44b6bb5d1f025

Observation 9ddb0a97-dc86-4a5a-87c4-6b7c7cc91587 · outbound

This paper cites Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning , year =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning , year =

Reference 4

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source=arxiv_source observed=2026-08-01T16:19:08.895307Z digest=sha256:814658365845e1747fbe4b24919c4accc6ff2166b14bc42d4e0b419175aaad1f

Observation 08bd99e6-43b5-409f-9c3d-20b276d6d977 · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 5

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source=arxiv_source observed=2026-08-01T16:19:08.900431Z digest=sha256:70d946a2aa1de0960f1c1bc80e7861017f4c173ab950b5ca9ee4d854d02f211f

Observation ee03b8a2-e8b7-4635-a8f0-7ed6c4f70668 · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 6

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Observation 9f3783fa-a504-4562-81f4-69a02777fb4e · outbound

This paper cites PR ompt Optimization in Multi-Step Tasks ( PROMST ): Integrating Human Feedback and Heuristic-based Sampling.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning PR ompt Optimization in Multi-Step Tasks ( PROMST ): Integrating Human Feedback and Heuristic-based Sampling

Reference 7

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Observation b7bef96f-70fd-45a5-bf66-51f318a13c8b · outbound

This paper cites Proceedings of the 34th International Conference on Machine Learning , year =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Proceedings of the 34th International Conference on Machine Learning , year =

Reference 8

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source=arxiv_source observed=2026-08-01T16:19:09.042591Z digest=sha256:ec2949adb201a3d80e793295b8041d6cd0ad4d4ca9d42361f921f4581c9147a3

Observation c450f7f2-0013-43a6-9f59-19974e7338fd · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 9

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source=arxiv_source observed=2026-08-01T16:19:09.047938Z digest=sha256:691125533663ae2d338211ec87ce3a8838fde9e2cb34a1288d1f50f9ba491a99

Observation da0d0288-592b-47cd-810b-ad5b39ab8ee3 · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 10

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source=arxiv_source observed=2026-08-01T16:19:09.052873Z digest=sha256:356bbe70effe3c1fb6b37878c9b53dbf87e4287bd78c699fab2d9f1ae3fa315f

Observation 331b90dd-02bf-4a3c-9079-1bf45daae6d1 · outbound

This paper cites PaLM - E : An embodied multimodal language model.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning PaLM - E : An embodied multimodal language model

Reference 11

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Observation ad1729b6-5ab0-4d98-a926-55736f07261c · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 12

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source=arxiv_source observed=2026-08-01T16:19:09.063031Z digest=sha256:24cbaff60848cb5ac29816542e01ae635b0767a35049cc67247269c677397282

Observation 9d29c639-e366-4146-9af6-e66ab469e635 · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 13

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source=arxiv_source observed=2026-08-01T16:19:09.068394Z digest=sha256:683bdef3be6fc528d271461d1ac0bca6a34cc333cb1144f1d04d970dc2c054fb

Observation ba6ac62c-c7dc-4e12-ae45-4d2d4eb5f053 · outbound

This paper cites Guiding Long-Horizon Task and Motion Planning with Vision Language Models , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Guiding Long-Horizon Task and Motion Planning with Vision Language Models , year=

Reference 14

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Observation 851ffedc-ef6f-460d-9c05-bfe57e2cd398 · outbound

This paper cites LLM -A*: Large Language Model Enhanced Incremental Heuristic Search on Path Planning.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning LLM -A*: Large Language Model Enhanced Incremental Heuristic Search on Path Planning

Reference 15

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source=arxiv_source observed=2026-08-01T16:19:09.078309Z digest=sha256:0263b9d32bf16911dd192216f10050030f6f052b9ed27dccc363157c2aefc904

Observation 9db15f77-75ed-49af-8772-a6188c318c80 · outbound

This paper cites Generalized planning in pddl domains with pretrained large language models.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Generalized planning in pddl domains with pretrained large language models

Reference 16

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source=arxiv_source observed=2026-08-01T16:19:09.083557Z digest=sha256:9a5fae8d3d4a09935fb920197271cf693f5cbadd8756fec967ee6febaa677168

Observation c4ad41f1-67ba-4dcc-8e11-b7eac6c3f06c · outbound

This paper cites Tree-Planner: Efficient Close-loop Task Planning with Large Language Models.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Tree-Planner: Efficient Close-loop Task Planning with Large Language Models

Reference 17

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source=arxiv_source observed=2026-08-01T16:19:09.088543Z digest=sha256:54cf6034ec0df6244b628279635dd55391699afded23d9dc6ecc4b85cdc7191b

Observation 1c3986bb-41d7-4c05-836e-ad1f329620b9 · outbound

This paper cites Thirty-seventh Conference on Neural Information Processing Systems , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Thirty-seventh Conference on Neural Information Processing Systems , year=

Reference 18

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Observation ccbbe1f9-e700-49b3-84df-6bdf58ab886f · outbound

This paper cites VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning

Reference 19

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Observation 2f8bca33-5877-49cd-b493-36ef59081fb2 · outbound

This paper cites Automated Planning Domain Inference for Task and Motion Planning , booktitle=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Automated Planning Domain Inference for Task and Motion Planning , booktitle=

Reference 20

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source=arxiv_source observed=2026-08-01T16:19:09.106401Z digest=sha256:ce38f8ae81c28a248f1f046ad12692f6bfcbc5ab6b86fe1bba70d1f6c1824411

Observation eb5d9207-258c-4d10-a281-22d8e7ef80e5 · outbound

This paper cites One demo is all it takes: Planning Domain Derivation with LLMs from A single demonstration.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning One demo is all it takes: Planning Domain Derivation with LLMs from A single demonstration

Reference 21

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source=arxiv_source observed=2026-08-01T16:19:09.112158Z digest=sha256:51830892b7436b9dba46b069e1373e4bdc417f81453ceb07117fdd334c5f5216

Observation 7399a969-a9e1-458c-9cfe-2df690f111e5 · outbound

This paper cites 2024 , booktitle =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 2024 , booktitle =

Reference 22

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source=arxiv_source observed=2026-08-01T16:19:09.120435Z digest=sha256:35e93b7a1b60484642edd268179784632fd33112a5f1c789a90195592bb56271

Observation 342ba355-c694-4cd7-aa68-3ac35ae4a6e2 · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 23

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source=arxiv_source observed=2026-08-01T16:19:09.125933Z digest=sha256:9938f5b8698dab3115604260ca2f2e3968b625aeffa88e903bd56942c99ea512

Observation 8028c919-bd06-4ea7-890e-6190f7a42de3 · outbound

This paper cites Predicate Invention for Bilevel Planning.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Predicate Invention for Bilevel Planning

Reference 24

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source=arxiv_source observed=2026-08-01T16:19:09.131648Z digest=sha256:57f27ebffda621131e26e1f62166618f253ae22b60f18d9183958e9f0e4af7ca

Observation 42925ab8-3207-4e44-84a0-67932f5b41db · outbound

This paper cites LLM+P: Empowering Large Language Models with Optimal Planning Proficiency.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 25

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source=arxiv_source observed=2026-08-01T16:19:09.138301Z digest=sha256:138e8b889469221730371e29064d6f420437bb0b81c28b63722c4a237803a015

Observation f7719203-b5ae-4277-bdc1-1cdb5a3b305f · outbound

This paper cites 2024 IEEE International conference on robotics and automation (ICRA) , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 2024 IEEE International conference on robotics and automation (ICRA) , year=

Reference 26

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source=arxiv_source observed=2026-08-01T16:19:09.144681Z digest=sha256:2c30a6cb7aad69ce10901ad701037e77427c9e19217072052d2479f3cefce22f

Observation 8dbcc4a3-dfc6-42df-9e7a-625bec2a16e3 · outbound

This paper cites Learning to Search in Task and Motion Planning With Streams.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Learning to Search in Task and Motion Planning With Streams

Reference 27

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source=arxiv_source observed=2026-08-01T16:19:09.151494Z digest=sha256:b81ed5c37f9c844aa83679bed450e1f5d7dc7ee59d95f1dc71f837063e625c1d

Observation 3a9f860a-ed8f-4561-93cc-faed0c1fc5e7 · outbound

This paper cites GPT-4o System Card.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning GPT-4o System Card

Reference 28

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source=arxiv_source observed=2026-08-01T16:19:09.157976Z digest=sha256:1a0eaf2a1c6793b46fa809cbc0650cf6c6926bc07f060fbfd61b9d9455671ed4

Observation 5a67648b-680c-4895-80ce-15ca3121df67 · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 29

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source=arxiv_source observed=2026-08-01T16:19:09.163871Z digest=sha256:c6c6babd5058be55d8a7a0ddcf62a69cec21aca314a1c6a5eb5ccc8414dd7e86

Observation d25f1995-52e9-40a3-ae6d-39bc27e86ba6 · outbound

This paper cites 8th Annual Conference on Robot Learning , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 8th Annual Conference on Robot Learning , year=

Reference 30

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source=arxiv_source observed=2026-08-01T16:19:09.169105Z digest=sha256:5e198b650910f82673e4e61646cbafdaf1a53f080ac123f8265847c1c64e315b

Observation 76d7cc7d-5525-4966-9697-10065ffc23dc · outbound

This paper cites 2025 IEEE International Conference on Robotics and Automation (ICRA) , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 2025 IEEE International Conference on Robotics and Automation (ICRA) , year=

Reference 31

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source=arxiv_source observed=2026-08-01T16:19:09.174066Z digest=sha256:04663a2d704abfd41dd9e5af4ebe6ce905176556c52257727232fcdee468607a

Observation 5f4c4e9f-4484-4758-84a2-190ae08a18a4 · outbound

This paper cites Language Models can infer action semantics for symbolic planners from environment feedback.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Language Models can infer action semantics for symbolic planners from environment feedback

Reference 32

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source=arxiv_source observed=2026-08-01T16:19:09.179437Z digest=sha256:a4ce88595f4e92b3b6083d68b900ad89dd9b08eb72cbf56e405f36348d78f707

Observation c557aa79-3ebc-493a-9432-4ac45b78b9e5 · outbound

This paper cites Robotics: Science and Systems (RSS) , year =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Robotics: Science and Systems (RSS) , year =

Reference 33

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source=arxiv_source observed=2026-08-01T16:19:09.184565Z digest=sha256:efe373965174db6385587abf43a2cff379b2a9795f8d223a94a7983f75e29a58

Observation 366571f6-5165-4293-8224-b875d778c5b2 · outbound

This paper cites Proceedings of The 7th Conference on Robot Learning , pages =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Proceedings of The 7th Conference on Robot Learning , pages =

Reference 34

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source=arxiv_source observed=2026-08-01T16:19:09.189293Z digest=sha256:bad25688f5b39df9390c75a2e1f2a5d8f18f243960d63e13b53d45eaeb39d2eb

Observation 52b6e325-2021-4b86-9976-209adcf764f6 · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 35

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source=arxiv_source observed=2026-08-01T16:19:09.194051Z digest=sha256:9134a06f767c597765af626de8d24acb35dcde314527d79ecf1fbd871e53fccc

Observation 56e4844a-dedb-41d5-8875-0436a2296903 · outbound

This paper cites 2023 , journal =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 2023 , journal =

Reference 36

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source=arxiv_source observed=2026-08-01T16:19:09.198996Z digest=sha256:e1fae1c0b4bfd756a8b5d8e6580fc8e56a31a24ee73450fed7aa1e4a3cc478d3

Observation 31fa4285-947b-4613-a0ba-bdc9b8098ffe · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 37

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source=arxiv_source observed=2026-08-01T16:19:09.204850Z digest=sha256:8065cf7b936afbfd0d3dd72f0147db39dbd4d73c19e8cfae81027f23f0ac9f4d

Observation 6f3a398b-73d5-4f09-8dff-8f28b532815f · outbound

This paper cites Self-training meets consistency: Improving LLMs’ reasoning with consistency-driven rationale evaluation.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Self-training meets consistency: Improving LLMs’ reasoning with consistency-driven rationale evaluation

Reference 38

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source=arxiv_source observed=2026-08-01T16:19:09.209734Z digest=sha256:6b1c0e37d14e20788fd49881620623f116ef424fa83ee1f7bbe969cac1d8ee84

Observation e070f32f-14e7-442c-b00e-40b1324bc62d · outbound

This paper cites V-STaR: Training verifiers for self-taught reasoners.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning V-STaR: Training verifiers for self-taught reasoners

Reference 39

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source=arxiv_source observed=2026-08-01T16:19:09.214874Z digest=sha256:a465d72d458e5e60ac0956d5c411b90b3df5af171fee8648bf6876f3cdb252fd

Observation 2fb42ef6-7560-41d7-99a0-565517381693 · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 40

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source=arxiv_source observed=2026-08-01T16:19:09.220151Z digest=sha256:33e3c6f64eb0798b97e352dcbe9577b054fbc226ece219522f64836025fa36cb

Observation 236b00c9-1fee-480c-8208-9ac6461ebb46 · outbound

This paper cites and Le, Quoc V.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning and Le, Quoc V

Reference 41

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source=arxiv_source observed=2026-08-01T16:19:09.224941Z digest=sha256:9c2df47b9d8be8af6cb71379b984267b283057cb06590b210ce0b62ec307182b

Observation 3d60e958-0207-4433-9d31-f50a34365a6e · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 42

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source=arxiv_source observed=2026-08-01T16:19:09.229618Z digest=sha256:552ec483316899c9f74afa26849c86578c05cc7232b538ee38f2e3777ee9bfbd

Observation e3dc2175-5fda-43b2-8536-f09aba7f95f2 · outbound

This paper cites International Conference on Learning Representations (ICLR) , year =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning International Conference on Learning Representations (ICLR) , year =

Reference 43

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source=arxiv_source observed=2026-08-01T16:19:09.234045Z digest=sha256:f005741fe01a6299cd875d9f95b3775f6af52c62c783c606971c2d6563b9a703

Observation d77fd5d9-f55b-47ae-99be-28db8a34a2f6 · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 44

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source=arxiv_source observed=2026-08-01T16:19:09.238622Z digest=sha256:415f8c3c0158575c741f6fb8ac7bca8fee33d159792c2d94ed3d81afc2c9b477

Observation 7fba14af-800d-4bc5-b538-08de23d1291f · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Training Verifiers to Solve Math Word Problems

Reference 45

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source=arxiv_source observed=2026-08-01T16:19:09.243340Z digest=sha256:76ed5aceadf601778f1d59857866965c661b10bc3e14d12b4dc3ff3abb99b056

Observation 0cdffd52-c250-4751-933c-e7d577151d28 · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 46

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source=arxiv_source observed=2026-08-01T16:19:09.249292Z digest=sha256:3b2155cd14cc3effa3ed518c9a3ab9dbf8bef6acf356cb17f6c42c63f3ac68c5

Observation 1175553e-4d32-46d6-9d45-62500ba0d4de · outbound

This paper cites 8th Annual Conference on Robot Learning , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 8th Annual Conference on Robot Learning , year=

Reference 47

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source=arxiv_source observed=2026-08-01T16:19:09.253853Z digest=sha256:a300dbc0c5789759a340d28011dc469f8cbc5f74779c89cbeafe184bc9b5d6bd

Observation f30c5824-cb0c-4a81-a5a3-995f6a5f8341 · outbound

This paper cites 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , year=

Reference 48

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source=arxiv_source observed=2026-08-01T16:19:09.258804Z digest=sha256:acf519380bf03494da74cb74f9d0952b22108e6f1362453e6c72d70441edb6af

Observation 64af1046-3b38-43a5-9256-ea29b081fba1 · outbound

This paper cites P roof W riter: Generating Implications, Proofs, and Abductive Statements over Natural Language.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning P roof W riter: Generating Implications, Proofs, and Abductive Statements over Natural Language

Reference 49

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source=arxiv_source observed=2026-08-01T16:19:09.264871Z digest=sha256:6d3ebde96ce10ec54f6ae4da5fc6e4f05533efde5b47eb92d300d34c09e41c40

Observation 68cb53c6-2c3a-42ee-9368-4731d2c8815a · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 50

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source=arxiv_source observed=2026-08-01T16:19:09.269954Z digest=sha256:cbaeed4c5d4442f1b43cd28157ca6a19893114abe30ad56324dbe059155cf6f4

Observation 193a4afe-7873-4da8-8e06-47275f672ed3 · outbound

This paper cites Annual Meeting of the Association for Computational Linguistics , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Annual Meeting of the Association for Computational Linguistics , year=

Reference 51

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source=arxiv_source observed=2026-08-01T16:19:09.276079Z digest=sha256:e57862b460ef1cd860d52ac2a97ccb75f6f51dbec476d42c3f23e3eb4e543dec

Observation dc6dffe1-a2c4-4f5a-80ea-bda9424cef8b · outbound

This paper cites Logic- LM : Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Logic- LM : Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning

Reference 52

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source=arxiv_source observed=2026-08-01T16:19:09.281687Z digest=sha256:5836bc0ef044b12bc2aab00cbc7c963dc785430fe7aeaf6d58d5b83b54d38db7

Observation ed4519b2-ca2b-4f5c-b02e-5e87731d6a03 · outbound

This paper cites FOLIO : Natural Language Reasoning with First-Order Logic.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning FOLIO : Natural Language Reasoning with First-Order Logic

Reference 53

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source=arxiv_source observed=2026-08-01T16:19:09.286511Z digest=sha256:3e8775c1b59be731c48c03f90e71fe9f20695679cad10bf9f146f4e48f6a3da1

Observation 8e5f5137-a548-441c-9947-9ed316c2253d · outbound

This paper cites LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers , booktitle=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers , booktitle=

Reference 54

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source=arxiv_source observed=2026-08-01T16:19:09.292056Z digest=sha256:bbfb027ed6f1c40859f5682f6b0ac27db62b1cc9ae7aaee44f97d5b7bd0ed21d

Observation 35184324-8d29-4914-9cf8-a712bf888661 · outbound

This paper cites Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA) , year =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA) , year =

Reference 55

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source=arxiv_source observed=2026-08-01T16:19:09.297221Z digest=sha256:a8c6034fc2d3a6db15a67ee37a8b5032a8a1e788ac23a318e96578c3dbed7e1f

Observation 0721eb25-5633-49f5-a6f6-aa49c436507d · outbound

This paper cites Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track , year=

Reference 56

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source=arxiv_source observed=2026-08-01T16:19:09.303527Z digest=sha256:84ec66263066fac5d2752616aa362fb14f675e0abb3a236324b47dafeaa1bcf4

Observation b68784c7-1726-41e2-93ad-5df7eb4b629e · outbound

This paper cites The FF planning system: Fast plan generation through heuristic search.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning The FF planning system: Fast plan generation through heuristic search

Reference 57

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source=arxiv_source observed=2026-08-01T16:19:09.308983Z digest=sha256:b0917a648802f84b512648f5af7bd4f088e1c3e8b806fcfc10e1f35ae2ced018

Observation 122dbe3f-90df-4180-8f53-ced7e282e3f5 · outbound

This paper cites and Khashabi, Daniel and Hajishirzi, Hannaneh.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning and Khashabi, Daniel and Hajishirzi, Hannaneh

Reference 58

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source=arxiv_source observed=2026-08-01T16:19:09.315365Z digest=sha256:a29480aa478a855dbfc413cbb7b9d1c2603019fa501d5ba128c56e3ce027257a

Observation 2c4a6624-ae57-446b-9696-6244640b806c · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 59

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source=arxiv_source observed=2026-08-01T16:19:09.320835Z digest=sha256:5b60d142b2b9eb5bc079e8bcc6808df25fc3b7327a93283ecd84b50ed5bfcec7

Observation 67965d00-bf82-4a5a-a9b7-545e7ca71af3 · outbound

This paper cites Gemma 3 Technical Report.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Gemma 3 Technical Report

Reference 60

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source=arxiv_source observed=2026-08-01T16:19:09.326564Z digest=sha256:519e4bd235289b0b02f6b6ec896de535a56de0294348522d56d56a8a089d4962

Observation 0d10358e-a338-489f-924a-d451b954988e · outbound

This paper cites Ministral 3.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Ministral 3

Reference 61

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source=arxiv_source observed=2026-08-01T16:19:09.332083Z digest=sha256:b37064bcffb3ecac45aef92695629003f7ab2cbe93b63739731047c5447969d7

Observation 88d4b2cf-b351-4a8a-bab4-5b398c6355be · outbound

This paper cites Distilling the Knowledge in a Neural Network.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Distilling the Knowledge in a Neural Network

Reference 62

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source=arxiv_source observed=2026-08-01T16:19:09.337678Z digest=sha256:9173e49f404fdd8acb53c823017c8193504eac4a70397c794f8f122dc91b90b3

Observation 9768e662-a595-4120-a7d0-4b7db0a43a51 · outbound

This paper cites _0 : A vision-language-action flow model for general robot control.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning _0 : A vision-language-action flow model for general robot control

Reference 63

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source=arxiv_source observed=2026-08-01T16:19:09.343450Z digest=sha256:613123cd5c7e4f88f597dd3096a118c7c5249094fc7c6e23c671e3f52a1a7f7b

Observation 16cc7e52-958e-4527-877e-a96ce3a233e8 · outbound

This paper cites Leveraging Language-based Representations for Better Solving Symbol-related Problems with Large Language Models.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Leveraging Language-based Representations for Better Solving Symbol-related Problems with Large Language Models

Reference 64

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source=arxiv_source observed=2026-08-01T16:19:09.349119Z digest=sha256:bdaeb3928916bc80a7d94ca005ea6646286d33f1639d00d255d2933f7c2cb34a

Observation 3adaad89-9cef-40c5-a83f-0917c14452ea · outbound

This paper cites Language Models can be Deductive Solvers.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Language Models can be Deductive Solvers

Reference 65

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source=arxiv_source observed=2026-08-01T16:19:09.355079Z digest=sha256:16f1af4138111689b8023655592e0f5c0e34cd30ed6a6ccd7c692930a1eecd62

Observation 386c7ae8-4e45-48f7-9706-3997fe250bb8 · outbound

This paper cites Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation , volume =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation , volume =

Reference 66

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source=arxiv_source observed=2026-08-01T16:19:09.362563Z digest=sha256:5e7a1c91e3eb145f7137c7e01726d4287b2ac8a91304751025e53854ceef6fdf

Observation 84d0d508-9c07-4ffd-8d21-8f5619ee4633 · outbound

This paper cites Proximal Policy Optimization Algorithms.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Proximal Policy Optimization Algorithms

Reference 67

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source=arxiv_source observed=2026-08-01T16:19:09.368721Z digest=sha256:a2d06a20e827e35e3e278bb2777b8f497a3af6c3b85425ebf45553210a23e683

Observation f3192980-ea8c-478f-b52b-43b95e4eb77e · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 68

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source=arxiv_source observed=2026-08-01T16:19:09.374881Z digest=sha256:7dc30ca4f4519fcd3d80638f78fffcd84c194c42c5998c9792e8c63358146e82

Observation b3c0e181-8742-4306-af4e-b6363ebb17b4 · outbound

This paper cites Deep Reinforcement Learning from Human Preferences , volume =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Deep Reinforcement Learning from Human Preferences , volume =

Reference 69

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source=arxiv_source observed=2026-08-01T16:19:09.380937Z digest=sha256:908b25d7a5331b4a5cd90dd48554239a96af4554fb8fcc95c0f62394f7123737

Observation 6aba837c-f80d-4286-b2c7-69ea156cd918 · outbound

This paper cites Thirty-seventh Conference on Neural Information Processing Systems , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Thirty-seventh Conference on Neural Information Processing Systems , year=

Reference 70

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source=arxiv_source observed=2026-08-01T16:19:09.386273Z digest=sha256:951e88b69e49c3e87e55aae0bc36b58c4ee9c90ee16e18747e6f6ca27260cdb0

Observation 3dbf8f4b-01a5-4e91-9379-21fc9772c2af · outbound

This paper cites 9th Annual Conference on Robot Learning , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 9th Annual Conference on Robot Learning , year=

Reference 71

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source=arxiv_source observed=2026-08-01T16:19:09.391007Z digest=sha256:3e11d88abd1e9e496968b258511624fdb259ee1229d3a47d6dced5575462687c

Observation 03fa7656-eb9d-4691-a703-5608e7023ba7 · outbound

This paper cites Proceedings of the International Conference on Automated Planning and Scheduling , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Proceedings of the International Conference on Automated Planning and Scheduling , year=

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source=arxiv_source observed=2026-08-01T16:19:09.396601Z digest=sha256:8bdcc42a602f9a7962a20f60d6053950037862156fddb7168681f11ba84eaa29

Observation 2239283a-12c9-4a36-a19e-0853b853a4db · outbound

This paper cites Understanding the Capabilities of Large Language Models for Automated Planning.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Understanding the Capabilities of Large Language Models for Automated Planning

Reference 73

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source=arxiv_source observed=2026-08-01T16:19:09.402294Z digest=sha256:752b0dd751d6e6893bd533f12d254ae50efb99fadb4d46858522fc2f67d2e3bf

Observation e98cc004-d6b8-4949-a73d-f6977041f784 · outbound

This paper cites 2026 , journal=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 2026 , journal=

Reference 74

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source=arxiv_source observed=2026-08-01T16:19:09.408284Z digest=sha256:38131c4ad0636202dc6cbd3c4e00918c9324e13a338ee20f9f8c8182150b5477

Observation 8b047dd4-0c94-41b6-8501-416bc3d13124 · outbound

This paper cites UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning , year =.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning , year =

Reference 75

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:09.413334Z digest=sha256:8f0d2ce074225b5a572df6b1f6029c6775fe781ef3be1fb0508b9af7b94fae8d

Observation 0fd56c30-abf1-46c4-9068-942911e35c7f · outbound

This paper cites MolmoAct2: Action Reasoning Models for Real-world Deployment.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning MolmoAct2: Action Reasoning Models for Real-world Deployment

Reference 76

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no resolver link, observed 2026-08-01T16:19:09.418294Z

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source=arxiv_source observed=2026-08-01T16:19:09.418294Z digest=sha256:7a951058f89aa2521d781cbc1d170ca9f94a9895c3c64f48a788601259b4211c

Observation 0de7cf1d-cdd9-432d-9325-fd708f1f43f5 · outbound

This paper cites X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model

Reference 77

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no resolver link, observed 2026-08-01T16:19:09.424307Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:09.424307Z digest=sha256:234c561e520811cd20ecf6b587fd0b8cbe57ea67e947603d6ec1983d823b1a2a

Observation 993161e1-81ee-4506-8e49-a96336842d7b · outbound

This paper cites arXiv preprint arXiv:2510.06710 , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning arXiv preprint arXiv:2510.06710 , year=

Reference 78

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no resolver link, observed 2026-08-01T16:19:09.429489Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:09.429489Z digest=sha256:c8aa454a69560c3f4224ae6a3004d66bb4cdcbbffd81fdc0577080af435f008a

Observation 8404be0f-8a2d-4a05-9835-6f3af5958e3f · outbound

This paper cites an unresolved cited work.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Unresolved cited work

Reference 79

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no resolver link, observed 2026-08-01T16:19:09.434371Z

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source=arxiv_source observed=2026-08-01T16:19:09.434371Z digest=sha256:0813443e85b6ca5e8268339b484fd3abd41ce087be8de033f6fefa6c3d86f646

Observation 413eb35c-9b51-476b-a2c2-22ed60b46607 · outbound

This paper cites 2011 IEEE international conference on robotics and automation , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 2011 IEEE international conference on robotics and automation , year=

Reference 80

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no resolver link, observed 2026-08-01T16:19:09.439332Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:09.439332Z digest=sha256:24d5b13ee80425ebf40bc0c8ceb07caca320136c47d491582e718ca5b2336ad5

Observation cb89ec46-e1c9-4afd-aec8-70d0fbc37ac2 · outbound

This paper cites Do World Action Models Generalize Better than VLAs? A Robustness Study.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Do World Action Models Generalize Better than VLAs? A Robustness Study

Reference 81

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no resolver link, observed 2026-08-01T16:19:09.444916Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:09.444916Z digest=sha256:e4630564bdaeef732b4c6c9ea4020a6382f8a4b782f4b7ddaaa55f3b6da4e3ae

Observation 7a540708-74bc-43b8-8cd1-3d182128b081 · outbound

This paper cites Annual review of control, robotics, and autonomous systems , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Annual review of control, robotics, and autonomous systems , year=

Reference 82

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no resolver link, observed 2026-08-01T16:19:09.450128Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:09.450128Z digest=sha256:b87edd0f16255498aac2bc441861224ed259858d267c21760f0aa9add4b11b24

Observation 5f8e3dfe-e0dc-41ab-8e25-ee744a8a2250 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning ReAct: Synergizing Reasoning and Acting in Language Models

Reference 83

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no resolver link, observed 2026-08-01T16:19:09.455113Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:09.455113Z digest=sha256:a28c6e244b29a9bbfc572390254732e7873a70115012fb9678482d505c4e4ca2

Observation 97345006-bf33-4082-8820-99b5bb833690 · outbound

This paper cites Advances in neural information processing systems , volume=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Advances in neural information processing systems , volume=

Reference 84

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no resolver link, observed 2026-08-01T16:19:09.460290Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:09.460290Z digest=sha256:364c27f51862edb5d8d938a16d918f89f059b752d967a8f0841a72fcff09d65d

Observation 2b97a56f-fcd6-4a6f-92e4-cfeaad0fe476 · outbound

This paper cites Advances in neural information processing systems , volume=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Advances in neural information processing systems , volume=

Reference 85

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no resolver link, observed 2026-08-01T16:19:09.465072Z

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source=arxiv_source observed=2026-08-01T16:19:09.465072Z digest=sha256:1f1728f119a3d71acaa64ba2479087303709241a9423d5218dd8dd3f773a9c3f

Observation 3b20f65b-7b73-444c-9cfc-f226553ece24 · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 86

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no resolver link, observed 2026-08-01T16:19:09.470463Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:19:09.470463Z digest=sha256:589fd7bccbb9f930efa2d2972e898da2568cb4da8ab661c09677982f61ca8be8

Observation 0dedd20b-5b70-4e36-88af-cd972d8a90a9 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Advances in Neural Information Processing Systems , volume=

Reference 87

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no resolver link, observed 2026-08-01T16:19:09.475525Z

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source=arxiv_source observed=2026-08-01T16:19:09.475525Z digest=sha256:869879c9c537f1247a7a823cfa247234749fa7920a117ebbb7981cd3060e9970

Observation 20932d70-a708-4e60-af4c-d2ce95c52491 · outbound

This paper cites Forty-first International Conference on Machine Learning , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Forty-first International Conference on Machine Learning , year=

Reference 88

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no resolver link, observed 2026-08-01T16:19:09.480544Z

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source=arxiv_source observed=2026-08-01T16:19:09.480544Z digest=sha256:23cbc9f6b06ad065a53e8b14522b4aaceede9fff3ec3d03f48bf0d6448e4ba75

Observation afd81873-b3d2-4616-a971-2b9be68ec250 · outbound

This paper cites International Conference on Learning Representations , volume=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning International Conference on Learning Representations , volume=

Reference 89

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no resolver link, observed 2026-08-01T16:19:09.485449Z

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source=arxiv_source observed=2026-08-01T16:19:09.485449Z digest=sha256:05ca8d842d33af1fbcc35cfd590bdbbe6b5ee89eabf4ff5ad25d8423e47c034e

Observation 155cc97a-b899-4669-ab69-3e3318f88127 · outbound

This paper cites Agentless: Demystifying LLM-based Software Engineering Agents.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Agentless: Demystifying LLM-based Software Engineering Agents

Reference 90

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source=arxiv_source observed=2026-08-01T16:19:09.490101Z digest=sha256:3e82f9979d033a4a62a661d3897e7dbfa44ab8dbe2ba8ffcfc23378c5930ec7f

Observation 2c4d3fea-cb97-42e4-b06d-7563bd1b4cbd · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 91

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no resolver link, observed 2026-08-01T16:19:09.495017Z

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source=arxiv_source observed=2026-08-01T16:19:09.495017Z digest=sha256:09007314792e2fb4036ea3b87c2313e3c738c1a51c29de8641d0905e2f7aad83

Observation a38d2ba1-daad-45b9-a850-97c755c34895 · outbound

This paper cites International Conference on Learning Representations , volume=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning International Conference on Learning Representations , volume=

Reference 92

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no resolver link, observed 2026-08-01T16:19:09.500613Z

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source=arxiv_source observed=2026-08-01T16:19:09.500613Z digest=sha256:680657e4d06bc9f7baa884e892204442ae65c2771050ba20257ec92f37df912e

Observation 241e74a7-28ce-465e-8792-b0562a9622d2 · outbound

This paper cites arXiv preprint arXiv:2603.11558 , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning arXiv preprint arXiv:2603.11558 , year=

Reference 93

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source=arxiv_source observed=2026-08-01T16:19:09.505369Z digest=sha256:bc1f620408dd1ad140708de58c1af5ab4b00cc7debd7a36de34fac382bc658fb

Observation 88c8f65c-5bb6-4bad-a27d-9229206d5fb7 · outbound

This paper cites ENPIRE: Agentic Robot Policy Self-Improvement in the Real World.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning ENPIRE: Agentic Robot Policy Self-Improvement in the Real World

Reference 94

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source=arxiv_source observed=2026-08-01T16:19:09.510548Z digest=sha256:99d8d32b87089aefd0df1f276837b09378a7e9b00ffdc7c340ed395adeef80a8

Observation c70183f4-4b1d-4dd2-a9d0-d500882a440d · outbound

This paper cites arXiv preprint arXiv:2602.11291 , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning arXiv preprint arXiv:2602.11291 , year=

Reference 95

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no resolver link, observed 2026-08-01T16:19:09.515542Z

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source=arxiv_source observed=2026-08-01T16:19:09.515542Z digest=sha256:dd9b4724e09e87cb06088fd8a72dcb49b77da94e0ca8cbafb83d849ec49f3f9e

Observation 8283fad7-38fe-4014-9bcd-750564a421fb · outbound

This paper cites Advances in neural information processing systems , volume=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Advances in neural information processing systems , volume=

Reference 96

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no resolver link, observed 2026-08-01T16:19:09.520953Z

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source=arxiv_source observed=2026-08-01T16:19:09.520953Z digest=sha256:def7508afeb0190b12e19e0fefc2b4ea042311e7c71638f6b9f005a067c9fdb1

Observation 723389e3-86bc-4ff5-96c2-99e4bda0cfda · outbound

This paper cites Adversarial Skill Chaining for Long-Horizon Robot Manipulation via Terminal State Regularization.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Adversarial Skill Chaining for Long-Horizon Robot Manipulation via Terminal State Regularization

Reference 97

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no resolver link, observed 2026-08-01T16:19:09.525689Z

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source=arxiv_source observed=2026-08-01T16:19:09.525689Z digest=sha256:d3dfb484de6bd7e2af87742637f51d5cb108d4685071ec06599115f70f5fe6b4

Observation 7fc1c70f-2394-4b92-af87-caac4c0b5ba7 · outbound

This paper cites International conference on learning representations , year=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning International conference on learning representations , year=

Reference 98

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source=arxiv_source observed=2026-08-01T16:19:09.530560Z digest=sha256:bcf236975b477845cf1bc84355e192581ac209d05bf9ccf1b24df9234e0f2b8d

Observation 6c914c8c-be2f-49f3-8af5-68f7ec6ab359 · outbound

This paper cites 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , pages=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , pages=

Reference 99

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no resolver link, observed 2026-08-01T16:19:09.535624Z

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source=arxiv_source observed=2026-08-01T16:19:09.535624Z digest=sha256:389f3ca128184b90d2f5858e5f4de3a20add97aac7477865b21564e36b9cc1c5

Observation 382273bf-450d-4a41-86cf-90737f854a14 · outbound

This paper cites Conference on Robot Learning , pages=.

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning Conference on Robot Learning , pages=

Reference 100

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source=arxiv_source observed=2026-08-01T16:19:09.540151Z digest=sha256:403e83142ce03bfb65e4541a0333517151d9ade1ae05b94c3eb3099678aed927

Pith citing papers

No inbound Pith citation observations are available.