Papers with attention analysis
From Redundancy to Relevance: Information Flow in LVLMs Across Reasoning Tasks (2025.naacl-long)
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Xiaofeng Zhang, Yihao Quan, Chen Shen, Xiaosong Yuan, Shaotian Yan, Liang Xie, Wenxiao Wang, Chaochen Gu, Hao Tang, Jieping Ye
| Challenge: | Large visionlanguage models (LVLMs) are a powerful visual-language reasoning tool. |
| Approach: | They propose to integrate attention analysis with LLaVA-CAM to determine interactions between visual representations. |
| Outcome: | The proposed approach can be used to determine interactions between visual representations. |
From Reasoning to Answer: Empirical, Attention-Based and Mechanistic Insights into Distilled DeepSeek R1 Models (2025.emnlp-main)
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| Challenge: | Large Reasoning Models generate explicit reasoning traces alongside final answers . the extent to which these traces influence answer generation remains unclear . |
| Approach: | They conduct empirical evaluation of Large Reasoning Models that include explicit reasoning . they also show that answer tokens attend substantially to reasoning tokens . |
| Outcome: | The results show that including explicit reasoning improves answer quality across domains . they also show that answer tokens attend substantially to reasoning tokens - the authors . |
Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers (2026.findings-acl)
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Van Yang, Shouren Wang, Debargha Ganguly, Xinpeng Li, Chaoda Song, Vikash Singh, Vipin Chaudhary, Xiaotian Han
| Challenge: | Explicit /think> tags are used to expose intermediate reasoning and enable hybrid thinking behaviors. |
| Approach: | They propose a training-free prompting format that combines these triggers to achieve intermediate-budget reasoning, outperforming fixed-token and prompt-based baselines in terms of the accuracy–length trade-off. |
| Outcome: | The proposed method outperforms fixed-token and prompt-based prompts in accuracy–length trade-offs while improving Qwen3-8B on AIME from 69.8% to 72.4% and on GPQA from 58.5% to 61.1%. |