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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 2026-08-11T06:34:44.6726+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
  • metadata mismatch0

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:a9bf1973e0d6522da41a2f534b3cd76a6c53de6199d08665b2e801d4d3c10beb

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:c1d05481ba2cfcf71bed89ee48ce922a000ce62a3f4aa8de2e4a1a0f5f2c2e05

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=sha256:135924b93eea2755a7a412007ba183d04c00addbc42f50d5f0b858d1ef029182

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=sha256:65b8f1a2dbd1b0a5e2dc9c0429322ac71289d7db903326920f465c08654adfe7

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:af95ab4ef76c905f5e1e4380f757aec23342ef68c7d004a18332b2b66a07d353

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=sha256:8814e91bd98a59133dda83d439475328e80d69d498d87ff6f81572cf07514269

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T15:50:34.424063Z digest=sha256:7fc6667fa29cd07719b0f0a85687ce5c2bcd1590ba372530b57cfd4a14f4b67a

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:f8714c36ee58a553191ac25876ae62c937cb1e0d5e22f596c48f2b0d607daa29

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=sha256:0b6ceaf9e732084ea53990848c3eec0a93caf16b813b64da1aa29c774f5356fa

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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T15:50:34.436340Z digest=sha256:2cbd1d019a48e85ee3b1e7a0a2ce24d8dcb96ddb3cba5581ea8e9329a22dfda3

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=sha256:8ba3567d9356bb6bb1c362f8966c057a44f6adf41dc6a1d9a4d7a694d236f6ea

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=sha256:7ed6b6bf981df5e2f78e905b23f62e9fe4e1c66935c4163b5515b16359f3702a

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=sha256:2896c3657575d5db3c0e98d86f66cba55a532b898c415f45a704339a8342443d

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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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-11T15:50:34.419839Z digest=sha256:c7916eb2adbeb1e863a9e28b6da362ec8beb877842882581e964b7c135a875f6

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:f1230f530ec82efe498bfb5e25804ddd54d70cac44520e625dcb4037c112253a

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=sha256:16be04faf3a7c7b41bdbbecc87c6212524b0651702fff02521da0122152eaf65

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=sha256:991bb39085b7974dcbf7c2ce2859bbeddb1a1c89d445ee02071e117bb5963de1

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=sha256:13629897f68a36db4f6cff4d7f589a07e6da3db9fbda8b2ca59ccb0881fe493b

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=sha256:0ba59307becfc037f99a1bec74c14fed54ffde6b24a34eeabce6992ad765192e

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=sha256:71b2c783b63c01eff3a356ceb9c09099e54397324754fd1bf2ed4c2721ae8565

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=sha256:7db1877da2d2c923b73915be8cb58aaeecf26775a4e848c954483eb80a3bd6ca

Pith citing papers

No inbound Pith citation observations are available.