Paper Citation Record · LEDGER

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning

As of 4 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2507.21545.

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

pith.paper-citation-record.v1
2507.21545 v3

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-19T03:00:28.619627Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:38:50.100301Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

52 of 52 outbound references displayed

verified exact12
verified fuzzy31
unresolved3
parse uncertain5
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e3226c06-d44a-462d-afb7-daa43e9b5ae5 · outbound

This paper cites GPT-4o System Card.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning GPT-4o System Card

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-05-19T03:02:00.229332Z

Source-reported events for the cited work

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Observation f90d8687-8010-46a5-bca0-073cfd68ea72 · outbound

This paper cites Qwen2.5-VL Technical Report.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Qwen2.5-VL Technical Report

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-19T03:02:00.254044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 50e94710-3bb0-4b21-8cbc-94d976b514ea · outbound

This paper cites On the Limit of Language Models as Planning Formalizers.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning On the Limit of Language Models as Planning Formalizers

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:02:00.223489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7710741c-2bc8-491e-9643-d793e6ebac23 · outbound

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

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-19T03:02:00.271746Z

Source-reported events for the cited work

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Observation 1cda5642-877c-4325-b549-ba29ce259818 · outbound

This paper cites Dynamic planning with an llm.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Dynamic planning with an llm

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.071155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f800f59d-87a0-4b78-a6ca-bd117e620c62 · outbound

This paper cites PDDLEGO: Iterative planning in textual environments.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning PDDLEGO: Iterative planning in textual environments

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:00.999865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 9595c129-2aa9-4143-9795-a394ea3abb1c · outbound

This paper cites Pddl| the planning domain definition language.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Pddl| the planning domain definition language

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:00.996007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7672e2d4-40c6-4782-b6c3-82e53c69bc20 · outbound

This paper cites The fast downward planning system.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning The fast downward planning system

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.067751Z

Source-reported events for the cited work

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Observation ab7ca8b1-c70d-4c7d-af0e-e9f98e497d6d · outbound

This paper cites AutoGPT+P: Affordance-based Task Planning with Large Language Models.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning AutoGPT+P: Affordance-based Task Planning with Large Language Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:02:00.248532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f3349fc3-269a-4257-bbb1-870a0a120dd6 · outbound

This paper cites Beltran-Hernandez, Masashi Hamaya, Atsushi Hashimoto, Shohei Tanaka, Kento Kawaharazuka, Kazutoshi Tanaka, Yoshitaka Ushiku, and Shinsuke Mori.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Beltran-Hernandez, Masashi Hamaya, Atsushi Hashimoto, Shohei Tanaka, Kento Kawaharazuka, Kazutoshi Tanaka, Yoshitaka Ushiku, and Shinsuke Mori

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.060452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8f5d3d98-c30f-4c20-b327-00edf2f38f66 · outbound

This paper cites Leveraging pre-trained large language models to construct and utilize world models for model-based task planning.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Leveraging pre-trained large language models to construct and utilize world models for model-based task planning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.064086Z

Source-reported events for the cited work

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Observation a8ff2a33-ce69-4a47-8e40-4c07ea76043e · outbound

This paper cites InterPreT: Interactive Predicate Learning from Language Feedback for Generalizable Task Planning.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning InterPreT: Interactive Predicate Learning from Language Feedback for Generalizable Task Planning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:02:00.236486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f8cb104c-381a-442a-ba34-d1437ac301bd · outbound

This paper cites Towards robust LLM-driven planning from minimal text descriptions.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Towards robust LLM-driven planning from minimal text descriptions

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.112649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 43bc93f2-b7dc-497b-b852-cd4d6834e169 · outbound

This paper cites Xiao, Fuxiang Frank Xia, Jie Fu, Ge Zhang, Ge lin, and Weiyang Liu.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Xiao, Fuxiang Frank Xia, Jie Fu, Ge Zhang, Ge lin, and Weiyang Liu

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.105149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 5aee7361-1685-4675-b16d-490c89e1e3fb · outbound

This paper cites RDT-1b: a diffusion foundation model for bimanual manipulation.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning RDT-1b: a diffusion foundation model for bimanual manipulation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.056757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 3d48b2b8-a8ea-4d20-b7c8-e16f92d8200e · outbound

This paper cites Open- VLA: An open-source vision-language-action model.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Open- VLA: An open-source vision-language-action model

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.100873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 75f31bca-a7dd-4bed-9efd-510d2fb6484c · outbound

This paper cites π0: A vision-language-action flow model for general robot control.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning π0: A vision-language-action flow model for general robot control

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.053275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 9461ca85-7448-415b-b222-bc69036eb035 · outbound

This paper cites DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-19T03:02:00.242136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 0ad70c8a-a1dc-45fe-9e9a-9be5a8e72395 · outbound

This paper cites A comprehensive survey on pretrained foundation models: A history from bert to chatgpt.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning A comprehensive survey on pretrained foundation models: A history from bert to chatgpt

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.074576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 382a2fc7-5f2b-49d9-b335-a77c54885048 · outbound

This paper cites A Survey on Post-training of Large Language Models.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning A Survey on Post-training of Large Language Models

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T03:02:00.195093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8c87d64e-5a31-4477-b220-d2bb600bb631 · outbound

This paper cites Code as policies: Language model programs for embodied control.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Code as policies: Language model programs for embodied control

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.082367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6c6f8147-3040-4e1f-8c0c-91b5c6424df8 · outbound

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

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning React: Synergizing reasoning and acting in language models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.038441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 21a0f813-95e9-4dac-8985-14371dcd3b9d · outbound

This paper cites Isr-llm: Iterative self-refined large language model for long-horizon sequential task planning.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Isr-llm: Iterative self-refined large language model for long-horizon sequential task planning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.089699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6daebac4-6581-4300-b665-5bdc8c72dbad · outbound

This paper cites DeepSeek-V3 Technical Report.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning DeepSeek-V3 Technical Report

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-19T03:02:00.265943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 09ead793-7ae8-4136-9b9c-050c5100a892 · outbound

This paper cites Progprompt: Generating situated robot task plans using large language models.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Progprompt: Generating situated robot task plans using large language models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.042114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 2a57e282-da19-483c-a615-2a511c89409a · outbound

This paper cites Do as i can, not as i say: Grounding language in robotic affordances.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Do as i can, not as i say: Grounding language in robotic affordances

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.135280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 91318d20-61d8-4381-a12d-fb39ed7ee890 · outbound

This paper cites Saycanpay: Heuristic planning with large language models using learnable domain knowledge.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Saycanpay: Heuristic planning with large language models using learnable domain knowledge

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.117209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 07a05b66-9777-4652-9f26-c43c3dff22ca · outbound

This paper cites 11 Innermonologue: Embodied reasoning through planning with language models.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning 11 Innermonologue: Embodied reasoning through planning with language models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.085663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 388ed4d0-c3f7-410d-8544-6aaef2426f91 · outbound

This paper cites Reflex- ion: language agents with verbal reinforcement learning.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Reflex- ion: language agents with verbal reinforcement learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.030649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1d1412c6-5eae-4d27-b09c-0b299e613330 · outbound

This paper cites Large language models as commonsense knowledge for large-scale task planning.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Large language models as commonsense knowledge for large-scale task planning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.026780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation b240b826-497b-4d24-ac9b-6961c70293a6 · outbound

This paper cites Chain- of-symbol prompting for spatial reasoning in large language models.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Chain- of-symbol prompting for spatial reasoning in large language models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.093469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8eecc735-3846-499d-bf01-423290d8052c · outbound

This paper cites Look before you leap: Unveiling the power of GPT-4v in robotic vision-language planning.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Look before you leap: Unveiling the power of GPT-4v in robotic vision-language planning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.034595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation cca08de5-e6c7-425e-9ca0-692e41cd9004 · outbound

This paper cites Siegel, Jiahai Feng, Noa Korneev, Joshua B.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Siegel, Jiahai Feng, Noa Korneev, Joshua B

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.045889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation bf8ba42b-d895-4332-a076-93b52fbddbc6 · outbound

This paper cites Language-Augmented Symbolic Planner for Open-World Task Planning.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Language-Augmented Symbolic Planner for Open-World Task Planning

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:02:00.216587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4e7b9673-4721-4401-a764-5ed22348b034 · outbound

This paper cites Learning compositional behaviors from demonstration and language.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Learning compositional behaviors from demonstration and language

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.016156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation b3f0f722-206f-4771-bf0b-b7a2316fb311 · outbound

This paper cites Predicate invention from pixels via pretrained vision-language models.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Predicate invention from pixels via pretrained vision-language models

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:02:00.260609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ca0fce66-150b-415d-87d4-b62fa0dbef87 · outbound

This paper cites Dexmimicgen: Automated data generation for bimanual dexterous manipulation via imitation learning.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Dexmimicgen: Automated data generation for bimanual dexterous manipulation via imitation learning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.023174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 66f7d2ca-ac6d-40f4-a312-e4049b90f6b3 · outbound

This paper cites You Only Teach Once: Learn One-Shot Bimanual Robotic Manipulation from Video Demonstrations.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning You Only Teach Once: Learn One-Shot Bimanual Robotic Manipulation from Video Demonstrations

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:02:00.209454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation acbccf83-cedc-4ac7-8eb8-8e225ef68a5f · outbound

This paper cites When Video Coding Meets Multimodal Large Language Models: A Unified Paradigm for Video Coding.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning When Video Coding Meets Multimodal Large Language Models: A Unified Paradigm for Video Coding

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:02:00.202644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 85d5fd77-2bac-419a-b968-ed011e6c73ec · outbound

This paper cites Learning transferable visual models from natural language supervision.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Learning transferable visual models from natural language supervision

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.008088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation c8c0de05-7f45-4c51-9aa5-44ed2864eb33 · outbound

This paper cites Sigmoid loss for language image pre-training.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Sigmoid loss for language image pre-training

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.131544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation abf367dc-fec3-4cfb-8068-23c48f9c8aec · outbound

This paper cites Mpnet: Masked and permuted pre-training for language understanding.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Mpnet: Masked and permuted pre-training for language understanding

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.139058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1d8d85dc-5ac3-4ead-af1f-bc68bd8f0403 · outbound

This paper cites an unresolved cited work.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.124146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation debb0652-b9b8-432b-b1a3-bff445d155cb · outbound

This paper cites an unresolved cited work.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.120563Z

Source-reported events for the cited work

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Observation 0979e6a7-8b7e-4286-a02b-96f2b942f423 · outbound

This paper cites Move the corn from the pot into the orange bowl, wipe the table with the towel in the drawer and put it back to the closed drawer.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Move the corn from the pot into the orange bowl, wipe the table with the towel in the drawer and put it back to the closed drawer

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.012241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 3ce16388-7fe6-4e2d-a3a7-276c00d0ced7 · outbound

This paper cites an unresolved cited work.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Unresolved cited work

Reference 46

Resolution: parse uncertain; raw_fallback, observed 2026-05-19T03:02:01.003605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation d988fde3-a5a7-4c86-a4d6-fe5d0f8c62c1 · outbound

This paper cites an unresolved cited work.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Unresolved cited work

Reference 47

Resolution: parse uncertain; raw_fallback, observed 2026-05-19T03:02:01.049772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8d6818e4-200c-4311-a99b-5564ba14d5c0 · outbound

This paper cites an unresolved cited work.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Unresolved cited work

Reference 48

Resolution: parse uncertain; raw_fallback, observed 2026-05-19T03:02:01.078732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f6e16dba-9621-42d2-add3-cbfdfb35043a · outbound

This paper cites an unresolved cited work.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-05-19T03:02:01.019579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation dcc5bfa4-7c75-45f6-bf09-6c30eddfffef · outbound

This paper cites an unresolved cited work.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Unresolved cited work

Reference 50

Resolution: parse uncertain; raw_fallback, observed 2026-05-19T03:02:01.127645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 64f7b14c-eaf4-4c82-9dc1-f1d67ae19f80 · outbound

This paper cites an unresolved cited work.

UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning Unresolved cited work

Reference 51

Resolution: parse uncertain; raw_fallback, observed 2026-05-19T03:02:01.097136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 898f32c5-1730-45f1-a40a-2745e4c4ea9a · outbound

This paper cites Move the corn from the pot into the orange bowl, wipe the table with the towel in the drawer and put it back to the closed drawer.

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T03:02:01.108973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Pith citing papers

Observation 7552e01a-c1be-4852-80dc-7ae7d0a02870 · inbound

PLanAR: Planning-Language-Grounded Agentic Reasoning for Robot Manipulation cites this paper.

PLanAR: Planning-Language-Grounded Agentic Reasoning for Robot Manipulation UniDomain: Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T05:38:50.100301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.