Papers with logical robustness
K-GIP: Diagnosing Logical Fractures in Large Vision-Language Models via Verification Scene Graphs and Sequential Pruning (2026.findings-acl)
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| Challenge: | Existing benchmarks that treat hallucinations as isolated errors neglect causal dependencies between visual perception and textual reasoning. |
| Approach: | They propose a Knowledge-Guided In-Context Probing framework that constructs a dual-perception ground truth to transform abstract priors into multi-granularity queries. |
| Outcome: | The proposed framework isolates deep reasoning failures from simple perceptual misses. |
Self-Training Meets Consistency: Improving LLMs’ Reasoning with Consistency-Driven Rationale Evaluation (2025.naacl-long)
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| Challenge: | Existing approaches labeled rationales that produce correct answers as appropriate for training but one measure risks misjudging rationale quality, leading models to learn flawed reasoning patterns. |
| Approach: | They propose a framework that evaluates rationales through follow-up questions and leverages this evaluation to guide its training. |
| Outcome: | The proposed framework improves robustness and correctness of rationales and reasoning abilities compared to previous self-training approaches. |