Paper Citation Record · LEDGER

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics

As of 7 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2507.21638.

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

pith.paper-citation-record.v1
2507.21638 v3

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:38:48.826346Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

23 of 23 outbound references displayed

verified exact2
verified fuzzy4
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 338d5c96-d2ae-45ce-b5b5-14473711127c · outbound

This paper cites Proprioception is information relating to robot configuration.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Proprioception is information relating to robot configuration

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:38:50.976202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 92cbf6df-ea15-4857-8db8-0c9d5cce467c · outbound

This paper cites Rihab Gorsane, Omayma Mahjoub, Ruan de Kock, Roland Dubb, Siddarth Singh, and Arnu Pre- torius.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Rihab Gorsane, Omayma Mahjoub, Ruan de Kock, Roland Dubb, Siddarth Singh, and Arnu Pre- torius

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:38:51.539578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0bb4ef67-3915-4716-bfda-4106ecd777a0 · outbound

This paper cites Component Formula Default Interpretation / Sweep Speed prefer- ence Pref(v; [vmin, vmax]) [0.06,0.14]m/s Rewards motion within the preferred speed range.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Component Formula Default Interpretation / Sweep Speed prefer- ence Pref(v; [vmin, vmax]) [0.06,0.14]m/s Rewards motion within the preferred speed range

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:38:50.824106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 60c22147-f5e2-4e06-be3f-b1fc088c6c23 · outbound

This paper cites RLlib: Abstractions for Distributed Reinforcement Learning.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics RLlib: Abstractions for Distributed Reinforcement Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:47.260154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 409589a0-401f-436a-9397-dd08dd0129e0 · outbound

This paper cites Eduardo Pignatelli, Jarek Liesen, Robert Tjarko Lange, Chris Lu, Pablo Samuel Castro, and Laura Toni.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Eduardo Pignatelli, Jarek Liesen, Robert Tjarko Lange, Chris Lu, Pablo Samuel Castro, and Laura Toni

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:47.690261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a3fca40-4cbb-49ed-9d0a-418037374cae · outbound

This paper cites NAVIX: Scaling MiniGrid Environments with JAX.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics NAVIX: Scaling MiniGrid Environments with JAX

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:47.781512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0194871e-549d-4501-beed-c52e8e1201a2 · outbound

This paper cites Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T12:38:49.950901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ffe6570-eb67-4bd3-968a-dfe37f36b4a5 · outbound

This paper cites URL https://doi.org/10.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics URL https://doi.org/10

Reference 15

Resolution: verified exact; doi, observed 2026-08-06T12:38:49.031635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d2909112-0244-44ab-ba2c-96653b0686f6 · outbound

This paper cites robosuite: A Modular Simulation Framework and Benchmark for Robot Learning.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics robosuite: A Modular Simulation Framework and Benchmark for Robot Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:48.634961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc814b80-c59d-4675-9fdb-ea8821ebf16b · outbound

This paper cites DOI: 10.1609/aaai.v24i1.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics DOI: 10.1609/aaai.v24i1

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:48.238489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 557e457d-86bc-446e-9b5d-605154dae2d9 · outbound

This paper cites Kevin Zakka, Baruch Tabanpour, Qiayuan Liao, Mustafa Haiderbhai, Samuel Holt, Jing Yuan Luo, Arthur Allshire, Erik Frey, Koushil Sreenath, Lueder A.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Kevin Zakka, Baruch Tabanpour, Qiayuan Liao, Mustafa Haiderbhai, Samuel Holt, Jing Yuan Luo, Arthur Allshire, Erik Frey, Koushil Sreenath, Lueder A

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:48.543894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8538401f-2784-4144-9cd5-8f640383bf1a · outbound

This paper cites Yuanpei Chen, Yaodong Yang, Tianhao Wu, Shengjie Wang, Xidong Feng, Jiechuan Jiang, Zongqing Lu, Stephen Marcus McAleer, Hao Dong, and Song-Chun Zhu.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Yuanpei Chen, Yaodong Yang, Tianhao Wu, Shengjie Wang, Xidong Feng, Jiechuan Jiang, Zongqing Lu, Stephen Marcus McAleer, Hao Dong, and Song-Chun Zhu

Reference 2013

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T12:38:50.579145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 01aa8147-083d-4c35-8711-8c1a9d9438ca · outbound

This paper cites On the Properties of Neural Machine Translation: Encoder-Decoder Approaches.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics On the Properties of Neural Machine Translation: Encoder-Decoder Approaches

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:46.821942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39625410-3e9b-434b-b50e-a3f0f59eaab1 · outbound

This paper cites DOI: 10.1007/978-3-319-28929-8_2.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics DOI: 10.1007/978-3-319-28929-8_2

Reference 2016

Resolution: verified exact; doi, observed 2026-08-06T12:38:49.312162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9751caa8-d661-4978-8224-1117b768ecdd · outbound

This paper cites Emanuel Todorov, Tom Erez, and Yuval Tassa.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Emanuel Todorov, Tom Erez, and Yuval Tassa

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:48.366746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 414267ad-c040-45d7-853f-a839425c73da · outbound

This paper cites Stefano V.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Stefano V

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:46.519393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef66e1c3-d6dc-4a40-a18f-1987bb5038a1 · outbound

This paper cites The StarCraft Multi-Agent Challenge.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics The StarCraft Multi-Agent Challenge

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:48.099267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 454ed1be-b442-4cd3-9d4f-a8b1117e6b7f · outbound

This paper cites an unresolved cited work.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Unresolved cited work

Reference 2020

Resolution: unresolved; raw_fallback, observed 2026-08-06T12:38:51.173400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation be0497ab-3a38-4fa9-a49f-2eeb5dbd12c0 · outbound

This paper cites Leveraging Procedural Generation to Benchmark Reinforcement Learning.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Leveraging Procedural Generation to Benchmark Reinforcement Learning

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:46.903783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1eeac36b-1f5f-48e4-9443-803a27b9467a · outbound

This paper cites Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:38:51.390284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 71490a6f-ab2a-4f1c-94e6-c2745c4af4c6 · outbound

This paper cites an unresolved cited work.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Unresolved cited work

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:47.365223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cedf5e4-2987-4804-8263-b0205314beb1 · outbound

This paper cites The Hanabi Challenge: A New Frontier for AI Research.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics The Hanabi Challenge: A New Frontier for AI Research

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:46.588417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4381ebaf-bfbf-461b-8352-e349532158be · outbound

This paper cites Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning.

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T12:38:47.493124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.