Saved in:
| Main Authors: | Wang, Olivia Peiyu, Bansal, Tashvi, Bai, Ryan, Chui, Emily M., Gilpin, Leilani H. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.09970 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Bridging Legal Interpretation and Formal Logic: Faithfulness, Assumption, and the Future of AI Legal Reasoning
by: Wang, Olivia Peiyu, et al.
Published: (2026)
by: Wang, Olivia Peiyu, et al.
Published: (2026)
Guaranteed Optimal Compositional Explanations for Neurons
by: La Rosa, Biagio, et al.
Published: (2025)
by: La Rosa, Biagio, et al.
Published: (2025)
Open Vocabulary Compositional Explanations for Neuron Alignment
by: La Rosa, Biagio, et al.
Published: (2025)
by: La Rosa, Biagio, et al.
Published: (2025)
Learning to Draw ASCII Improves Spatial Reasoning in Language Models
by: Huang, Shiyuan, et al.
Published: (2026)
by: Huang, Shiyuan, et al.
Published: (2026)
ProSLM : A Prolog Synergized Language Model for explainable Domain Specific Knowledge Based Question Answering
by: Vakharia, Priyesh, et al.
Published: (2024)
by: Vakharia, Priyesh, et al.
Published: (2024)
Reason from Fallacy: Enhancing Large Language Models' Logical Reasoning through Logical Fallacy Understanding
by: Li, Yanda, et al.
Published: (2024)
by: Li, Yanda, et al.
Published: (2024)
The Patsy Paradox: The Logical Fallacy of the Malicious AI
by: Harper, Osei
Published: (2026)
by: Harper, Osei
Published: (2026)
MisSynth: Improving MISSCI Logical Fallacies Classification with Synthetic Data
by: Poliakov, Mykhailo, et al.
Published: (2025)
by: Poliakov, Mykhailo, et al.
Published: (2025)
LLMs Are Prone to Fallacies in Causal Inference
by: Joshi, Nitish, et al.
Published: (2024)
by: Joshi, Nitish, et al.
Published: (2024)
A Logical Fallacy-Informed Framework for Argument Generation
by: Mouchel, Luca, et al.
Published: (2024)
by: Mouchel, Luca, et al.
Published: (2024)
Evaluation of an LLM in Identifying Logical Fallacies: A Call for Rigor When Adopting LLMs in HCI Research
by: Lim, Gionnieve, et al.
Published: (2024)
by: Lim, Gionnieve, et al.
Published: (2024)
Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs
by: Nahar, Mahjabin, et al.
Published: (2026)
by: Nahar, Mahjabin, et al.
Published: (2026)
Leveraging Context for Multimodal Fallacy Classification in Political Debates
by: Pittiglio, Alessio
Published: (2025)
by: Pittiglio, Alessio
Published: (2025)
Right this way: Can VLMs Guide Us to See More to Answer Questions?
by: Liu, Li, et al.
Published: (2024)
by: Liu, Li, et al.
Published: (2024)
The Average Patient Fallacy
by: Azhir, Alaleh, et al.
Published: (2025)
by: Azhir, Alaleh, et al.
Published: (2025)
VFSI: Validity First Spatial Intelligence for Constraint-Guided Traffic Diffusion
by: Chauhan, Kargi, et al.
Published: (2025)
by: Chauhan, Kargi, et al.
Published: (2025)
Tackling the Root of Misinformation by Teaching Laypeople about Logical Fallacies via Socratic Questioning and Critical Argumentation
by: Shi, Minjing, et al.
Published: (2026)
by: Shi, Minjing, et al.
Published: (2026)
Theory-Grounded Evaluation of Human-Like Fallacy Patterns in LLM Reasoning
by: Richardson, Andrew Keenan, et al.
Published: (2025)
by: Richardson, Andrew Keenan, et al.
Published: (2025)
Explore the Loss space with Hill-ADAM
by: Manikandan, Meenakshi, et al.
Published: (2025)
by: Manikandan, Meenakshi, et al.
Published: (2025)
MAFALDA: A Benchmark and Comprehensive Study of Fallacy Detection and Classification
by: Helwe, Chadi, et al.
Published: (2023)
by: Helwe, Chadi, et al.
Published: (2023)
Autoformalizing Natural Language to First-Order Logic: A Case Study in Logical Fallacy Detection
by: Lalwani, Abhinav, et al.
Published: (2024)
by: Lalwani, Abhinav, et al.
Published: (2024)
RSQ: Learning from Important Tokens Leads to Better Quantized LLMs
by: Sung, Yi-Lin, et al.
Published: (2025)
by: Sung, Yi-Lin, et al.
Published: (2025)
Addressing Logical Fallacies In Scientific Reasoning From Large Language Models: Towards a Dual-Inference Training Framework
by: Walker, Peter B., et al.
Published: (2025)
by: Walker, Peter B., et al.
Published: (2025)
FastV-RAG: Towards Fast and Fine-Grained Video QA with Retrieval-Augmented Generation
by: Li, Gen, et al.
Published: (2026)
by: Li, Gen, et al.
Published: (2026)
Tacit Knowledge Extraction via Logic Augmented Generation and Active Inference
by: Lamazzi, Lorenzo, et al.
Published: (2026)
by: Lamazzi, Lorenzo, et al.
Published: (2026)
AtlasKV: Augmenting LLMs with Billion-Scale Knowledge Graphs in 20GB VRAM
by: Huang, Haoyu, et al.
Published: (2025)
by: Huang, Haoyu, et al.
Published: (2025)
Large Language Models Are Better Logical Fallacy Reasoners with Counterargument, Explanation, and Goal-Aware Prompt Formulation
by: Jeong, Jiwon, et al.
Published: (2025)
by: Jeong, Jiwon, et al.
Published: (2025)
The Limits of AI Data Transparency Policy: Three Disclosure Fallacies
by: Shen, Judy Hanwen, et al.
Published: (2026)
by: Shen, Judy Hanwen, et al.
Published: (2026)
Customized Retrieval-Augmented Generation with LLM for Debiasing Recommendation Unlearning
by: Zhang, Haichao, et al.
Published: (2025)
by: Zhang, Haichao, et al.
Published: (2025)
Knowledge-enhanced Multimodal ECG Representation Learning with Arbitrary-Lead Inputs
by: Liu, Che, et al.
Published: (2025)
by: Liu, Che, et al.
Published: (2025)
Can We Count on LLMs? The Fixed-Effect Fallacy and Claims of GPT-4 Capabilities
by: Ball, Thomas, et al.
Published: (2024)
by: Ball, Thomas, et al.
Published: (2024)
Linking Knowledge to Care: Knowledge Graph-Augmented Medical Follow-Up Question Generation
by: Sun, Liwen, et al.
Published: (2026)
by: Sun, Liwen, et al.
Published: (2026)
Improving Neural-based Classification with Logical Background Knowledge
by: Ledaguenel, Arthur, et al.
Published: (2024)
by: Ledaguenel, Arthur, et al.
Published: (2024)
PAVE: Premise-Aware Validation and Editing for Retrieval-Augmented LLMs
by: Huang, Tianyi, et al.
Published: (2026)
by: Huang, Tianyi, et al.
Published: (2026)
Integrating Expert Knowledge into Logical Programs via LLMs
by: Górski, Franciszek, et al.
Published: (2025)
by: Górski, Franciszek, et al.
Published: (2025)
Controllable Logical Hypothesis Generation for Abductive Reasoning in Knowledge Graphs
by: Gao, Yisen, et al.
Published: (2025)
by: Gao, Yisen, et al.
Published: (2025)
Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems
by: Qi, Zhenting, et al.
Published: (2024)
by: Qi, Zhenting, et al.
Published: (2024)
Advancing Abductive Reasoning in Knowledge Graphs through Complex Logical Hypothesis Generation
by: Bai, Jiaxin, et al.
Published: (2023)
by: Bai, Jiaxin, et al.
Published: (2023)
Analyizing the Conjunction Fallacy as a Fact
by: Veloz, Tomas, et al.
Published: (2024)
by: Veloz, Tomas, et al.
Published: (2024)
The LLM Fallacy: Misattribution in AI-Assisted Cognitive Workflows
by: Kim, Hyunwoo, et al.
Published: (2026)
by: Kim, Hyunwoo, et al.
Published: (2026)
Similar Items
-
Bridging Legal Interpretation and Formal Logic: Faithfulness, Assumption, and the Future of AI Legal Reasoning
by: Wang, Olivia Peiyu, et al.
Published: (2026) -
Guaranteed Optimal Compositional Explanations for Neurons
by: La Rosa, Biagio, et al.
Published: (2025) -
Open Vocabulary Compositional Explanations for Neuron Alignment
by: La Rosa, Biagio, et al.
Published: (2025) -
Learning to Draw ASCII Improves Spatial Reasoning in Language Models
by: Huang, Shiyuan, et al.
Published: (2026) -
ProSLM : A Prolog Synergized Language Model for explainable Domain Specific Knowledge Based Question Answering
by: Vakharia, Priyesh, et al.
Published: (2024)