Paper Citation Record · LEDGER

Bilevel Learning for Bilevel Planning

As of 8 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 4 inbound Pith citation observations for arXiv:2502.08697.

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

pith.paper-citation-record.v1
2502.08697 v3

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T00:02:02.712285Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T16:45:44.659577Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T17:27:14.845260Z

Reference resolution

66 of 66 outbound references displayed

verified exact0
verified fuzzy53
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0326365a-0a89-434e-9077-758fb111fa85 · outbound

This paper cites MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations.

Bilevel Learning for Bilevel Planning MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:01.959293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31b0a8b4-803e-4b6b-9a18-472fadb02788 · outbound

This paper cites Dif- fusion policy: Visuomotor policy learning via action diffusion.

Bilevel Learning for Bilevel Planning Dif- fusion policy: Visuomotor policy learning via action diffusion

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:04.039975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7df9b183-4647-4e4f-977e-30befc5ea49d · outbound

This paper cites Learning fine-grained bimanual manipulation with low-cost hardware.

Bilevel Learning for Bilevel Planning Learning fine-grained bimanual manipulation with low-cost hardware

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:04.024618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4567d14a-51e1-49f5-8ae3-75f869a276fe · outbound

This paper cites Equivariant Diffusion Policy.

Bilevel Learning for Bilevel Planning Equivariant Diffusion Policy

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:01.974683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 716a7269-828e-47a6-98d8-8ed082127130 · outbound

This paper cites EquiBot: SIM(3)-Equivariant Diffusion Policy for Generalizable and Data Efficient Learning.

Bilevel Learning for Bilevel Planning EquiBot: SIM(3)-Equivariant Diffusion Policy for Generalizable and Data Efficient Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:01.979758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df035090-0b92-49dd-ba8e-8073ee00bba2 · outbound

This paper cites What Planning Problems Can A Relational Neural Network Solve? In Proceedings of the Advances in Neural Information Processing Systems (NeurIPS), volume 36, 2024.

Bilevel Learning for Bilevel Planning What Planning Problems Can A Relational Neural Network Solve? In Proceedings of the Advances in Neural Information Processing Systems (NeurIPS), volume 36, 2024

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:04.009768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4d5e351d-b84b-45a7-88a9-36d879d980c7 · outbound

This paper cites LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation.

Bilevel Learning for Bilevel Planning LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.994572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 80f51088-a42f-4096-a682-0872851c023d · outbound

This paper cites Towards a unified theory of state abstraction for mdps.

Bilevel Learning for Bilevel Planning Towards a unified theory of state abstraction for mdps

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.979600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5540c254-5698-4e82-aaea-1e18e3513c62 · outbound

This paper cites State abstractions for lifelong reinforce- ment learning.

Bilevel Learning for Bilevel Planning State abstractions for lifelong reinforce- ment learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.964999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 99c1452d-d3ad-4fac-afbe-d4afbab2e437 · outbound

This paper cites From skills to symbols: Learning symbolic representations for abstract high-level planning.

Bilevel Learning for Bilevel Planning From skills to symbols: Learning symbolic representations for abstract high-level planning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.950414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 264217f9-0841-4f20-97f3-303dfdf38e82 · outbound

This paper cites Learning Grounded Action Abstrac- tions From Language.

Bilevel Learning for Bilevel Planning Learning Grounded Action Abstrac- tions From Language

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.935398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 744425cc-9f97-4f3b-8ee4-c2b27b790073 · outbound

This paper cites Discovering State And Action Abstractions For Generalized Task And Motion Planning.

Bilevel Learning for Bilevel Planning Discovering State And Action Abstractions For Generalized Task And Motion Planning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.920498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 97c8481f-b937-4ffa-a03a-86b22b2c4401 · outbound

This paper cites Guiding Long-Horizon Task and Motion Planning with Vision Language Models, 2024.

Bilevel Learning for Bilevel Planning Guiding Long-Horizon Task and Motion Planning with Vision Language Models, 2024

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.905829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b5b160d9-2c7e-4cc9-b265-91b864b06b5f · outbound

This paper cites From Reals to Logic and Back: Inventing Symbolic V ocabularies, Actions and Models for Planning from Raw Data.

Bilevel Learning for Bilevel Planning From Reals to Logic and Back: Inventing Symbolic V ocabularies, Actions and Models for Planning from Raw Data

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:02.021533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc5fbc7a-0d1e-4059-bbe0-4f0e7be9513e · outbound

This paper cites Learning Symbolic Operators for Task and Motion Planning.

Bilevel Learning for Bilevel Planning Learning Symbolic Operators for Task and Motion Planning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.890708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c1da0b19-3b57-4001-a4e9-d29233096ce3 · outbound

This paper cites Tenenbaum, Tom´as Lozano-P´erez, and Leslie Pack Kaelbling.

Bilevel Learning for Bilevel Planning Tenenbaum, Tom´as Lozano-P´erez, and Leslie Pack Kaelbling

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.875999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8e3bd6a3-d139-462b-9a8c-2bbafcbec695 · outbound

This paper cites Predicate Invention for Bilevel Planning.

Bilevel Learning for Bilevel Planning Predicate Invention for Bilevel Planning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.861351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 541f9a5b-403b-4fbe-a2b1-7881cb7d6777 · outbound

This paper cites GLIB: Efficient Exploration for Relational Model-Based Rein- forcement Learning via Goal-Literal Babbling.

Bilevel Learning for Bilevel Planning GLIB: Efficient Exploration for Relational Model-Based Rein- forcement Learning via Goal-Literal Babbling

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.846961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 70ba1a4c-6702-4eeb-9b7c-ed56d64a698a · outbound

This paper cites Practice Makes Perfect: Planning To Learn Skill Parameter Policies.

Bilevel Learning for Bilevel Planning Practice Makes Perfect: Planning To Learn Skill Parameter Policies

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.832933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 303dba06-a92d-4d7a-8a53-eea8ed85deba · outbound

This paper cites Learning Efficient Abstract Planning Models That Choose What to Predict.

Bilevel Learning for Bilevel Planning Learning Efficient Abstract Planning Models That Choose What to Predict

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.818007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a108b778-3859-451f-a05f-3eb4141e533a · outbound

This paper cites VisualPredicator: Learning Abstract World Models With Neuro-Symbolic Predicates For Robot Planning, 2024.

Bilevel Learning for Bilevel Planning VisualPredicator: Learning Abstract World Models With Neuro-Symbolic Predicates For Robot Planning, 2024

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.803533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 45328fc2-1f90-45c9-b959-eb963ad11f8c · outbound

This paper cites Active learning for teaching a robot grounded relational symbols.

Bilevel Learning for Bilevel Planning Active learning for teaching a robot grounded relational symbols

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.788351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 334e3079-9ece-4fa6-a929-20fe5b30c823 · outbound

This paper cites From skills to symbols: Learning symbolic representations for abstract high-level planning.

Bilevel Learning for Bilevel Planning From skills to symbols: Learning symbolic representations for abstract high-level planning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.773870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fc4614d0-aec0-4fbb-a6fd-3fbca09455b1 · outbound

This paper cites Embodied Active Learning of Relational State Abstractions for Bilevel Planning.

Bilevel Learning for Bilevel Planning Embodied Active Learning of Relational State Abstractions for Bilevel Planning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.759222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a332e0f7-2085-4d34-9f74-f4dd6123d8ee · outbound

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

Bilevel Learning for Bilevel Planning InterPreT: Interactive Predicate Learning from Language Feedback for Generalizable Task Planning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:02.257233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ebb3843-8fcf-49d8-b65e-6338c81d83a0 · outbound

This paper cites Grounding Predi- cates through Actions.

Bilevel Learning for Bilevel Planning Grounding Predi- cates through Actions

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.744638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0f1ba871-3f0c-4294-8692-0278e7b569d2 · outbound

This paper cites Classical Planning in Deep Latent Space: Bridging the Subsymbolic-Symbolic Boundary.

Bilevel Learning for Bilevel Planning Classical Planning in Deep Latent Space: Bridging the Subsymbolic-Symbolic Boundary

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.730233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 27a1ec22-b6c4-4ac3-a815-91d326191c2e · outbound

This paper cites Unsupervised Grounding of Plannable First-Order Logic Representation From Images.

Bilevel Learning for Bilevel Planning Unsupervised Grounding of Plannable First-Order Logic Representation From Images

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.715223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 85c202c9-dca0-4b79-9623-e5a81aaa8691 · outbound

This paper cites Learning Neural- Dymbolic Descriptive Planning Models via Cube-Space Priors: the V oyage Home (to STRIPS).

Bilevel Learning for Bilevel Planning Learning Neural- Dymbolic Descriptive Planning Models via Cube-Space Priors: the V oyage Home (to STRIPS)

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.700663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6b64f9f0-bc78-4e11-86f2-a6bf03d1ca08 · outbound

This paper cites Bisimulation Makes Analogies in Goal-conditioned Reinforcement Learning.

Bilevel Learning for Bilevel Planning Bisimulation Makes Analogies in Goal-conditioned Reinforcement Learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.685952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 926c4f14-35f1-41e8-9c48-36d556b8e4c0 · outbound

This paper cites Predicate Invention from Pixels via Pretrained Vision- Language Models.

Bilevel Learning for Bilevel Planning Predicate Invention from Pixels via Pretrained Vision- Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:02.331349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fe75e69-dc02-4643-9bb8-6acb04dd54a3 · outbound

This paper cites Tenenbaum, Tom ´as Lozano-P´erez, and Leslie Pack Kaelbling.

Bilevel Learning for Bilevel Planning Tenenbaum, Tom ´as Lozano-P´erez, and Leslie Pack Kaelbling

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.670631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 931b0a2a-f353-45cd-be28-fe1ec787192b · outbound

This paper cites Integrated Task and Motion Planning.

Bilevel Learning for Bilevel Planning Integrated Task and Motion Planning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.655638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e3b8946a-4a4c-49b2-b1f0-e0bd42eb1aa6 · outbound

This paper cites The Fast Downward Planning System.

Bilevel Learning for Bilevel Planning The Fast Downward Planning System

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.641328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1e44301e-8acb-4c70-8a27-11c1481fb1d7 · outbound

This paper cites Divergence Measures based on the Shannon Entropy.

Bilevel Learning for Bilevel Planning Divergence Measures based on the Shannon Entropy

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.627207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b1b0e948-9031-42d0-974c-4e43a648ab9f · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Bilevel Learning for Bilevel Planning Adam: A Method for Stochastic Optimization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:02.352118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8f42a3c-6364-4135-af7f-09659ee6d0d0 · outbound

This paper cites Learning Representations by Back-propagating Errors.

Bilevel Learning for Bilevel Planning Learning Representations by Back-propagating Errors

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.613560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 00a61b2d-735b-48fe-b9d4-d17c62afb946 · outbound

This paper cites Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search.

Bilevel Learning for Bilevel Planning Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.599355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 31b455eb-09bd-4380-bdae-bffc7b6a478b · outbound

This paper cites Mastering the Game of Go without Human Knowledge.

Bilevel Learning for Bilevel Planning Mastering the Game of Go without Human Knowledge

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.584454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dd7120fd-3e4e-4f23-9ebb-22c0ad794732 · outbound

This paper cites Relational inductive biases, deep learning, and graph networks.

Bilevel Learning for Bilevel Planning Relational inductive biases, deep learning, and graph networks

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:02.370621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcb2ec7f-4e2e-4bcc-8bdf-8de31168ef10 · outbound

This paper cites Attention is All You Need.

Bilevel Learning for Bilevel Planning Attention is All You Need

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.570113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 84da41bf-2548-410c-8a30-61fc3c31f0b3 · outbound

This paper cites Language Segment-Anything.

Bilevel Learning for Bilevel Planning Language Segment-Anything

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.555057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f9f3b928-b772-40e5-8316-fe629386fddd · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Bilevel Learning for Bilevel Planning SAM 2: Segment Anything in Images and Videos

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:02.385466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0730161-90a8-4444-8f8e-a9ac27596195 · outbound

This paper cites Hi- erarchical Task and Motion Planning in the Now.

Bilevel Learning for Bilevel Planning Hi- erarchical Task and Motion Planning in the Now

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.540368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 08709afb-bbfd-4c04-b0d2-71b94608cef7 · outbound

This paper cites Relay Policy Learning: Solv- ing Long-Horizon Tasks via Imitation and Reinforcement Learning.

Bilevel Learning for Bilevel Planning Relay Policy Learning: Solv- ing Long-Horizon Tasks via Imitation and Reinforcement Learning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.524580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation af89e26f-eed6-4db9-b055-9049d1b771d4 · outbound

This paper cites Augment- ing Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks.

Bilevel Learning for Bilevel Planning Augment- ing Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.509365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 22e74c44-d1fc-449d-b250-19e5d666ed63 · outbound

This paper cites Neural Logic Machines.

Bilevel Learning for Bilevel Planning Neural Logic Machines

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.494687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e3239d39-70fe-4543-b9d2-cd750de34acd · outbound

This paper cites Directed-Info GAIL: Learning Hierar- chical Policies from Unsegmented Demonstrations using Directed Information.

Bilevel Learning for Bilevel Planning Directed-Info GAIL: Learning Hierar- chical Policies from Unsegmented Demonstrations using Directed Information

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.480811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6b67e16e-219f-4432-879a-af83de231bc7 · outbound

This paper cites Compile: Compositional Imitation Learning and Execution.

Bilevel Learning for Bilevel Planning Compile: Compositional Imitation Learning and Execution

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.465799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d8e6f83c-2ae8-4e7d-bf34-74856bca85f4 · outbound

This paper cites PDSketch: Integrated Domain Programming, Learning, and Planning.

Bilevel Learning for Bilevel Planning PDSketch: Integrated Domain Programming, Learning, and Planning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.450762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fbbe30fd-8da4-4eba-80e7-9fd3ac01f6fa · outbound

This paper cites BLADE: Learning Compositional Behaviors from Demonstration and Language.

Bilevel Learning for Bilevel Planning BLADE: Learning Compositional Behaviors from Demonstration and Language

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.435543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 38a74271-8fa9-47a3-96a3-284f4c9ab682 · outbound

This paper cites Keypoint Abstraction using Large Models for Object-Relative Imitation Learning.

Bilevel Learning for Bilevel Planning Keypoint Abstraction using Large Models for Object-Relative Imitation Learning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:02.441073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7ef2d09-9bc0-4442-b7a1-cfbe2676eb1b · outbound

This paper cites Gener- alized Planning in PDDL Domains with Pretrained Large Language Models.

Bilevel Learning for Bilevel Planning Gener- alized Planning in PDDL Domains with Pretrained Large Language Models

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.420376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e190f1f7-7668-4561-90db-6eff55621c47 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Bilevel Learning for Bilevel Planning Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.403843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6302c8cb-a72e-4e4e-9a39-eaab1e11a65b · outbound

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

Bilevel Learning for Bilevel Planning V oxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.345882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5406b303-0436-4e37-9c41-6f9c14b71bb2 · outbound

This paper cites Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning.

Bilevel Learning for Bilevel Planning Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:02.506842Z

Source-reported events for the cited work

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Observation 9130dc0e-c63e-46d2-89b6-2cce8b41c63a · outbound

This paper cites Open-World Task and Motion Planning via Vision-Language Model Inferred Constraints.

Bilevel Learning for Bilevel Planning Open-World Task and Motion Planning via Vision-Language Model Inferred Constraints

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.299133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fbdadb50-cc9d-45e3-ae10-d27d95dae3df · outbound

This paper cites Pddlstream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning.

Bilevel Learning for Bilevel Planning Pddlstream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.283063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 86c4d678-dc42-4bf9-b633-e65007eac2fc · outbound

This paper cites Howe, Craig A.

Bilevel Learning for Bilevel Planning Howe, Craig A

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.269228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 30457b50-e26d-44b6-81d4-cd215f6cbf1a · outbound

This paper cites Anytime Motion Plan- ning using the RRT.

Bilevel Learning for Bilevel Planning Anytime Motion Plan- ning using the RRT

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.254039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 98133825-cf77-4f0c-8f51-da39b9721b0d · outbound

This paper cites Skill-based curiosity for intrinsically motivated reinforcement learning.

Bilevel Learning for Bilevel Planning Skill-based curiosity for intrinsically motivated reinforcement learning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.237553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1b0df965-515b-4cde-ac18-31cec39199a5 · outbound

This paper cites an unresolved cited work.

Bilevel Learning for Bilevel Planning Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-08T00:02:03.222191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation eae53c3a-5bc0-4270-b721-8bec9c026028 · outbound

This paper cites Hybrid Declarative-Imperative Representations for Hybrid Discrete-Continuous Decision- Making.

Bilevel Learning for Bilevel Planning Hybrid Declarative-Imperative Representations for Hybrid Discrete-Continuous Decision- Making

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.207468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0a4183f1-ae7a-4bbc-b0dd-ea14d8dba546 · outbound

This paper cites Accelerating 3D Deep Learning with PyTorch3D.

Bilevel Learning for Bilevel Planning Accelerating 3D Deep Learning with PyTorch3D

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-08T00:02:02.701278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23e4bab2-569f-4fd2-a3b6-677c68b2bfbf · outbound

This paper cites Pointnet: Deep Learning on Point Sets for 3D Classification and Segmentation.

Bilevel Learning for Bilevel Planning Pointnet: Deep Learning on Point Sets for 3D Classification and Segmentation

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.191507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d8d51992-c589-4f38-aab1-d642afbf875e · outbound

This paper cites grounded on.

Bilevel Learning for Bilevel Planning grounded on

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T00:02:03.174874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation 85f9aea1-a2d2-4b68-a08e-1230a856a198 · inbound

Emergent Neural Automaton Policies: Learning Symbolic Structure from Visuomotor Trajectories cites this paper.

Emergent Neural Automaton Policies: Learning Symbolic Structure from Visuomotor Trajectories Bilevel Learning for Bilevel Planning

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:08:21.427216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 268a69ea-c732-49c7-a9d4-d401610b4903 · inbound

Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs cites this paper.

Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs Bilevel Learning for Bilevel Planning

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:35:57.417210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ed6e7735-852e-4f3e-a9d4-68d2d292925e · inbound

Learning Compositional Symbolic Task Rules from Demonstrations with Inductive Logic Programming cites this paper.

Learning Compositional Symbolic Task Rules from Demonstrations with Inductive Logic Programming Bilevel Learning for Bilevel Planning

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-06-29T16:53:41.325972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9f2311c5-76f7-49f2-92e2-cf25cb7c8283 · inbound

Neuro-Symbolic Learning for Long-Horizon Task Planning Under Complex Logical Constraints cites this paper.

Neuro-Symbolic Learning for Long-Horizon Task Planning Under Complex Logical Constraints Bilevel Learning for Bilevel Planning

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-02T17:27:14.847930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.