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Paper Citation Record · LEDGER

HarnessWAM: Bridging Prediction and Deliberation in World Action Models

As of 12 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2608.09516.

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

pith.paper-citation-record.v1
2608.09516 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:50:34.444730Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

21 of 21 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved18
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 101ae6d0-9316-4da9-a681-6909ba930707 · outbound

This paper cites Unpacking Failure Modes of Generative Policies: Runtime Monitoring of Consistency and Progress.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models Unpacking Failure Modes of Generative Policies: Runtime Monitoring of Consistency and Progress

Reference 1

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source=pdf_text observed=2026-08-11T15:50:34.356082Z digest=sha256:dade4b18c556e5b62ca9a3b4c9b3e321ae819cbdd0ae8005c638c56c27a834b8

Observation b9960660-c0d1-4305-8324-2920aeffaa9f · outbound

This paper cites RoboMME: Benchmarking and Understanding Memory for Robotic Generalist Policies.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models RoboMME: Benchmarking and Understanding Memory for Robotic Generalist Policies

Reference 5

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source=pdf_text observed=2026-08-11T15:50:34.376400Z digest=sha256:8ad5dc1638b5c9bb54c70c04870920c67d6bb8dafb2347e410cadd8600e7511e

Observation 25a85bda-89ea-4183-84a5-128bfe1b6bf2 · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models OpenVLA: An Open-Source Vision-Language-Action Model

Reference 10

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source=pdf_text observed=2026-08-11T15:50:34.399036Z digest=sha256:93495dfd1b1c0971faf67a1577c813e143c2f02f160b645485f939fabb3a9f97

Observation 794c889e-6302-467e-8f92-e4b084dfd022 · outbound

This paper cites RoboMemArena: A Comprehensive and Challenging Robotic Memory Benchmark.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models RoboMemArena: A Comprehensive and Challenging Robotic Memory Benchmark

Reference 11

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source=pdf_text observed=2026-08-11T15:50:34.403105Z digest=sha256:3ffa2cbc64ab75809cc55ccda3ad2b2a2e016a0e6f20a2db1c69bbe9d9566e4a

Observation 782dba21-5ebb-4200-8edc-23647c955ba4 · outbound

This paper cites Causal World Modeling for Robot Control.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models Causal World Modeling for Robot Control

Reference 12

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source=pdf_text observed=2026-08-11T15:50:34.407477Z digest=sha256:be0bfb4e40e8c3951c9b11f13eef0fb21140c253720bc95f17b7c3a7ccd88d29

Observation 5a178790-6687-4079-8404-b0d43bb9d4b3 · outbound

This paper cites Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation

Reference 13

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source=pdf_text observed=2026-08-11T15:50:34.411581Z digest=sha256:0d784ff38a325e2dd52c2beb61d121df449e4dcd8e0f07f6ccf0ec573184b780

Observation 4ed896f7-4762-498a-bd84-7b47ab3f8e69 · outbound

This paper cites Scaling up memory for robotic control via experience retrieval.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models Scaling up memory for robotic control via experience retrieval

Reference 16

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:50:34.424063Z digest=sha256:d85e8fefb596a4f973eb9a88bea2116e75010f104d850df39378f1bff9e1f5f7

Observation fef7fdb0-68cd-4072-a223-77ff303fa8cb · outbound

This paper cites HiMem-WAM: Hierarchical Memory-Gated World Action Models for Robotic Manipulation.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models HiMem-WAM: Hierarchical Memory-Gated World Action Models for Robotic Manipulation

Reference 17

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source=pdf_text observed=2026-08-11T15:50:34.428143Z digest=sha256:b8711d886ab6788017aed05772219575f0a45ea07291cb07ed0fce0e94f63c37

Observation 98dccfe5-d3c7-46cb-a06e-9eb78b0bc011 · outbound

This paper cites MemoryWAM: Efficient World Action Modeling with Persistent Memory.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models MemoryWAM: Efficient World Action Modeling with Persistent Memory

Reference 18

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source=pdf_text observed=2026-08-11T15:50:34.432360Z digest=sha256:cec2afaf746fbc40975d0784cd5fb74cc571f95928847bf2f9fede111ca9e92b

Observation 70b5d3f4-38e0-4e11-913f-be7d3c0d0f75 · outbound

This paper cites React: Synergizing reasoning and acting in language models.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models React: Synergizing reasoning and acting in language models

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:50:34.436340Z digest=sha256:2e6f5619fb0d45addeb02b8bcd485718531a595b666512c253ef350edb710752

Observation b88af22b-0666-4dc1-a477-065575c40951 · outbound

This paper cites World Action Models are Zero-shot Policies.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models World Action Models are Zero-shot Policies

Reference 20

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source=pdf_text observed=2026-08-11T15:50:34.440686Z digest=sha256:eb9c873088efb77815c99bdfce32813e14e25dbd3f43ac34bc4a10ed6fc890fd

Observation 9559049e-5a1b-40ea-8d39-661ce2da4a39 · outbound

This paper cites Fast-WAM: Do World Action Models Need Test-time Future Imagination?.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models Fast-WAM: Do World Action Models Need Test-time Future Imagination?

Reference 21

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source=pdf_text observed=2026-08-11T15:50:34.444730Z digest=sha256:480a22ad507b4d48a9f28b53073d7dd7c45b8b262e561216adc6a0270ab7960a

Observation 98d318a8-ce40-4622-a6c9-51ef7770e971 · outbound

This paper cites SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Robot Task Planning.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Robot Task Planning

Reference 1997

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source=pdf_text observed=2026-08-11T15:50:34.415778Z digest=sha256:0d89b13d68a7f759eb074562199bf2295e9a40627c92604a1dab5385aad802d7

Observation 843b0bfc-41b2-4f46-a836-9a7c0960c231 · outbound

This paper cites Memoryvla: Perceptual-cognitive memory in vision-language- action models for robotic manipulation.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models Memoryvla: Perceptual-cognitive memory in vision-language- action models for robotic manipulation

Reference 1998

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T15:50:34.419839Z digest=sha256:a65805e6f8dc806747b06826b5ad10aea7c116e04bb4267edc51018129ae7d93

Observation 1162f116-863b-44cc-9852-9d00f303a192 · outbound

This paper cites SARM: Stage-Aware Reward Modeling for Long Horizon Robot Manipulation.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models SARM: Stage-Aware Reward Modeling for Long Horizon Robot Manipulation

Reference 2013

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source=pdf_text observed=2026-08-11T15:50:34.366892Z digest=sha256:d224491a59ced0af3a949ed37291411c1595f3d4bf5abacd06044fc3067b39a0

Observation 05f2813a-738d-43f4-967a-f0cb59a80eb8 · outbound

This paper cites Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control

Reference 2017

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source=pdf_text observed=2026-08-11T15:50:34.380935Z digest=sha256:e01a363d08143d9290d4aa99a7c3e39ed7c6b10751b9bd69cc48b0fa66c90cc0

Observation 479eb3e4-62a9-4d2b-910a-77945f534836 · outbound

This paper cites VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models

Reference 2022

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source=pdf_text observed=2026-08-11T15:50:34.390575Z digest=sha256:d40032bcf75995ec8672f2e37e253004617b49134e617e68fb91a048118b7801

Observation 69331f4b-dae3-4705-9f4b-4e5d0494bec3 · outbound

This paper cites $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization

Reference 2023

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source=pdf_text observed=2026-08-11T15:50:34.394727Z digest=sha256:729a4ff76843a30c2deffad8860e4f190df0aa3a05ba2066121abc4b4ef662c0

Observation 07a199eb-f5ff-426c-a404-ba546f4b03c3 · outbound

This paper cites Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 2024

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source=pdf_text observed=2026-08-11T15:50:34.361746Z digest=sha256:e0a0ec310e657876a3d9245cef332d4c0b9308dc0284d71131f6616b42552e71

Observation 7ad7f77b-3253-47ac-9edb-7a852eb2f2ac · outbound

This paper cites RH20T-P: A Primitive-Level Robotic Dataset Towards Composable Generalization Agents.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models RH20T-P: A Primitive-Level Robotic Dataset Towards Composable Generalization Agents

Reference 2025

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source=pdf_text observed=2026-08-11T15:50:34.371778Z digest=sha256:82c26b2d83b909de869b5a30a11ad58c8694c87bfa12d2f5362878d5cc632f45

Observation b55dd2e1-1bf3-4ae6-b766-d8adddf7014e · outbound

This paper cites Inner Monologue: Embodied Reasoning through Planning with Language Models.

HarnessWAM: Bridging Prediction and Deliberation in World Action Models Inner Monologue: Embodied Reasoning through Planning with Language Models

Reference 2026

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source=pdf_text observed=2026-08-11T15:50:34.386232Z digest=sha256:70f04fda9d21f5eaa3eace67416885e80cdcc629426b5d420a15fdd2312c7bdc

Pith citing papers

No inbound Pith citation observations are available.