Distilling Answer Set Programming Theories from Large Language Models | Paper Citation Record

Observation b9413df2-ff3d-481d-998c-d9ae4255855d · outbound

This paper cites The Stable Model Semantics for Logic Programming , booktitle =.

Distilling Answer Set Programming Theories from Large Language Models The Stable Model Semantics for Logic Programming , booktitle =

Reference 1

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Observation 9a1f15ee-38c4-4030-b5b5-cbc25bf6abfa · outbound

This paper cites Theory Pract.

Distilling Answer Set Programming Theories from Large Language Models Theory Pract

Reference 2

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Observation cb3bfb25-1798-4dac-82cb-b70dee812be0 · outbound

This paper cites Lawrence Zitnick and Devi Parikh , title =.

Distilling Answer Set Programming Theories from Large Language Models Lawrence Zitnick and Devi Parikh , title =

Reference 3

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Observation f085244e-629a-4eac-b7e3-a824585bf421 · outbound

This paper cites Making the.

Distilling Answer Set Programming Theories from Large Language Models Making the

Reference 4

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Distilling Answer Set Programming Theories from Large Language Models Unresolved cited work

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Observation 1e5e7346-e357-437b-b32b-8b974e095086 · outbound

This paper cites Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations , journal =.

Distilling Answer Set Programming Theories from Large Language Models Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations , journal =

Reference 6

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Observation 1a81e886-d175-47ff-a15c-89320a25cb4b · outbound

This paper cites Hudson and Christopher D.

Distilling Answer Set Programming Theories from Large Language Models Hudson and Christopher D

Reference 7

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Observation 1b8eadb9-76b6-4deb-82fd-602e0d909d01 · outbound

This paper cites Tenenbaum , title =.

Distilling Answer Set Programming Theories from Large Language Models Tenenbaum , title =

Reference 8

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Observation 63c984cb-de53-4191-8df0-3dca61ba4b34 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Unresolved cited work

Reference 9

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Observation efcb6c3c-e973-4542-8c2f-24709d40d823 · outbound

This paper cites Inferring and Executing Programs for Visual Reasoning , booktitle =.

Distilling Answer Set Programming Theories from Large Language Models Inferring and Executing Programs for Visual Reasoning , booktitle =

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.769034Z

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Observation 7ef89d37-2d9c-4e71-8189-559ca08e637f · outbound

This paper cites Hudson and Christopher D.

Distilling Answer Set Programming Theories from Large Language Models Hudson and Christopher D

Reference 11

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Observation 280f5e6a-d9fa-446b-9ba0-680310064ae3 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Neural-Symbolic

Reference 12

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Observation c216d71b-b539-423a-9fe8-c58e1cd899af · outbound

This paper cites Tenenbaum and Jiajun Wu , title =.

Distilling Answer Set Programming Theories from Large Language Models Tenenbaum and Jiajun Wu , title =

Reference 13

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Observation 85e7b69a-bbdb-4649-a315-8f123d75b1d9 · outbound

This paper cites DeepProbLog: Neural Probabilistic Logic Programming , booktitle =.

Distilling Answer Set Programming Theories from Large Language Models DeepProbLog: Neural Probabilistic Logic Programming , booktitle =

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.781142Z

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Observation 68e75fea-b913-4783-a5a7-33f6481c6894 · outbound

This paper cites d'Avila Garcez , editor =.

Distilling Answer Set Programming Theories from Large Language Models d'Avila Garcez , editor =

Reference 15

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Observation 9e824d48-06ef-471e-9412-f6eefc160741 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Neurosymbolic

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.787272Z

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Observation 7bbd0bb5-3795-4402-b29e-c861f7aeba67 · outbound

This paper cites Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text , booktitle =.

Distilling Answer Set Programming Theories from Large Language Models Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text , booktitle =

Reference 17

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Observation 2472e784-e351-479f-a1c3-a74d3819d1d2 · outbound

This paper cites Leveraging Large Language Models to Generate Answer Set Programs , booktitle =.

Distilling Answer Set Programming Theories from Large Language Models Leveraging Large Language Models to Generate Answer Set Programs , booktitle =

Reference 18

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Distilling Answer Set Programming Theories from Large Language Models Proceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning (KR) , pages =

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.796039Z

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Observation 461c53e8-6c1e-4a6d-aa09-f8c121c0c58e · outbound

This paper cites Trinh and Yuhuai Wu and Quoc V.

Distilling Answer Set Programming Theories from Large Language Models Trinh and Yuhuai Wu and Quoc V

Reference 20

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Observation cfcfac2c-1c29-421d-add7-d3ec4631646f · outbound

This paper cites Theory and Practice of Logic Programming , year =.

Distilling Answer Set Programming Theories from Large Language Models Theory and Practice of Logic Programming , year =

Reference 21

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Observation 7065355c-d973-4bc6-aa6f-2f35e75c2136 · outbound

This paper cites Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence,.

Distilling Answer Set Programming Theories from Large Language Models Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence,

Reference 22

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Observation bcd1a3e6-de13-478c-8f27-f380328fa686 · outbound

This paper cites Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning (.

Distilling Answer Set Programming Theories from Large Language Models Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning (

Reference 23

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Distilling Answer Set Programming Theories from Large Language Models Unresolved cited work

Reference 24

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Observation 5179c65f-dff5-442a-9165-c07e123175e9 · outbound

This paper cites Jimenez and John Yang and Alexander Wettig and Shunyu Yao and Kexin Pei and Ofir Press and Karthik R.

Distilling Answer Set Programming Theories from Large Language Models Jimenez and John Yang and Alexander Wettig and Shunyu Yao and Kexin Pei and Ofir Press and Karthik R

Reference 26

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Observation 4bc32e7f-6b82-4b4f-8d93-5308190d0524 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Jimenez and Alexander Wettig and Kilian Lieret and Shunyu Yao and Karthik Narasimhan and Ofir Press , editor =

Reference 27

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Distilling Answer Set Programming Theories from Large Language Models AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.824956Z

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Observation 65a1515b-f5de-4bf2-abfb-eb0ea619ec18 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Unresolved cited work

Reference 29

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Observation 686cc2f1-6372-4cb8-913e-6664cf89a776 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Chi and Quoc V

Reference 30

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Observation c7878477-849e-4e26-90bd-8ed6d6efab7c · outbound

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Distilling Answer Set Programming Theories from Large Language Models Large Language Models are Zero-Shot Reasoners , booktitle =

Reference 31

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Distilling Answer Set Programming Theories from Large Language Models Le and Ed H

Reference 32

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Observation 22a1c0a4-236d-49be-bd05-daf2e254a1e0 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Tree of Thoughts: Deliberate Problem Solving with Large Language Models , booktitle =

Reference 33

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Observation 5ffca07d-eb81-419a-88eb-775bc0cf7822 · outbound

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Distilling Answer Set Programming Theories from Large Language Models International Conference on Machine Learning,

Reference 34

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Observation 0a3b1ad1-3ee2-43a0-9ccf-ce400dfccde7 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Cohen , title =

Reference 35

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Distilling Answer Set Programming Theories from Large Language Models A Solver-in-the-Loop Framework for Improving LLMs on Answer Set Programming for Logic Puzzle Solving , booktitle =

Reference 38

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Distilling Answer Set Programming Theories from Large Language Models Theory and Practice of Logic Programming , year =

Reference 39

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Distilling Answer Set Programming Theories from Large Language Models Neural module networks

Reference 40

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Distilling Answer Set Programming Theories from Large Language Models The Claude 4 model family: Sonnet, opus, and haiku

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Distilling Answer Set Programming Theories from Large Language Models Lawrence Zitnick, and Devi Parikh

Reference 42

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Distilling Answer Set Programming Theories from Large Language Models Unresolved cited work

Reference 43

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Distilling Answer Set Programming Theories from Large Language Models Fine-tuning llms for answer set programming

Reference 44

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Observation 4514eb5b-cb92-466a-800e-cf9c09a38e2d · outbound

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Distilling Answer Set Programming Theories from Large Language Models Unresolved cited work

Reference 45

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Distilling Answer Set Programming Theories from Large Language Models DeepSeek-V4 technical report

Reference 46

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Distilling Answer Set Programming Theories from Large Language Models d'Avila Garcez

Reference 47

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Distilling Answer Set Programming Theories from Large Language Models A neuro-symbolic ASP pipeline for visual question answering

Reference 48

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Distilling Answer Set Programming Theories from Large Language Models A logic-based approach to contrastive explainability for neurosymbolic visual question answering

Reference 49

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Observation 60f55313-fc1b-4a2d-919f-f9c00e5e472d · outbound

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Distilling Answer Set Programming Theories from Large Language Models A modular neurosymbolic approach for visual graph question answering

Reference 50

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Distilling Answer Set Programming Theories from Large Language Models Declarative Knowledge Distillation from Large Language Models for Visual Question Answering Datasets

Reference 51

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Distilling Answer Set Programming Theories from Large Language Models PAL: program-aided language models

Reference 52

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Distilling Answer Set Programming Theories from Large Language Models Multi-shot ASP solving with clingo

Reference 53

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Distilling Answer Set Programming Theories from Large Language Models The stable model semantics for logic programming

Reference 54

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Distilling Answer Set Programming Theories from Large Language Models Making the V in VQA matter: Elevating the role of image understanding in visual question answering

Reference 55

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Distilling Answer Set Programming Theories from Large Language Models Distilling the Knowledge in a Neural Network

Reference 56

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Distilling Answer Set Programming Theories from Large Language Models Hudson and Christopher D

Reference 57

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Distilling Answer Set Programming Theories from Large Language Models Hudson and Christopher D

Reference 58

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Distilling Answer Set Programming Theories from Large Language Models Leveraging large language models to generate answer set programs

Reference 59

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Distilling Answer Set Programming Theories from Large Language Models Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik R

Reference 60

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Distilling Answer Set Programming Theories from Large Language Models Lawrence Zitnick, and Ross B

Reference 61

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Observation c0b9fc6b-9224-461f-b067-e1895d5497bf · outbound

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Distilling Answer Set Programming Theories from Large Language Models Lawrence Zitnick, and Ross B

Reference 62

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Observation 81cc32d6-bef6-451b-adfb-bb622abf7603 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Large language models are zero-shot reasoners

Reference 63

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Observation 77de2dec-2d13-47da-b93c-d8f0eae60937 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Shamma, Michael S

Reference 64

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Distilling Answer Set Programming Theories from Large Language Models Deepproblog: Neural probabilistic logic programming

Reference 65

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Distilling Answer Set Programming Theories from Large Language Models Tenenbaum, and Jiajun Wu

Reference 66

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Distilling Answer Set Programming Theories from Large Language Models GPT-5 system card

Reference 67

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.943358Z

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Observation 77a9b12c-eff1-4ed8-8ad9-25629c3b4ba6 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Can llms solve ASP problems? insights from a benchmarking study

Reference 68

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Observation 1e3252a2-a2c5-4d65-a7df-5afc6be37117 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Question answering with LLMs and learning from answer sets

Reference 69

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Observation 728e535b-9a20-4b3b-8b60-3c276ab8e9e8 · outbound

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Distilling Answer Set Programming Theories from Large Language Models A solver-in-the-loop framework for improving llms on answer set programming for logic puzzle solving

Reference 70

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Distilling Answer Set Programming Theories from Large Language Models Trinh, Yuhuai Wu, Quoc V

Reference 71

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Observation 50e6b725-25a6-4ae1-9526-341d9cf937b9 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Voyager: An open-ended embodied agent with large language models

Reference 72

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Observation 1bfb9efd-7bfe-48cc-b3b6-f47678dd3365 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Le, Ed H

Reference 73

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Distilling Answer Set Programming Theories from Large Language Models Chi, Quoc V

Reference 74

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.965345Z

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Observation 500b9811-5503-4419-91fc-d8de620a5c3b · outbound

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Distilling Answer Set Programming Theories from Large Language Models AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 75

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Observation 8e2514bf-a5e2-42d9-b7e5-edc129ddba6b · outbound

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Distilling Answer Set Programming Theories from Large Language Models Jimenez, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, and Ofir Press

Reference 76

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.972107Z

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Observation 72023f50-6aa6-4bcf-b3d7-c4a03e5ef508 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Coupling large language models with logic programming for robust and general reasoning from text

Reference 77

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Observation afea1234-52dd-4126-99c8-60e7f53f5152 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Learning to solve constraint satisfaction problems with large language models and answer set programming

Reference 78

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.979033Z

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Observation 31bc2116-e327-424e-bfca-c238b7a07e74 · outbound

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Distilling Answer Set Programming Theories from Large Language Models Tree of thoughts: Deliberate problem solving with large language models

Reference 79

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.981929Z

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Observation 88b76e1c-4898-49ec-b5f2-e46f3302a53d · outbound

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Distilling Answer Set Programming Theories from Large Language Models Neural-symbolic VQA: disentangling reasoning from vision and language understanding

Reference 80

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.984816Z

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Observation 657e1aad-ba13-4837-a309-8e367a2445e3 · outbound

This paper cites Tenenbaum.

Distilling Answer Set Programming Theories from Large Language Models Tenenbaum

Reference 81

Resolution: unresolved; no resolver link, observed 2026-07-31T18:15:10.987827Z

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