Papers with analytical reasoning
Uni-MMMU: A Massive Multi-discipline Multimodal Unified Benchmark (2026.acl-long)
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Kai Zou, Ziqi Huang, Yuhao Dong, Shulin Tian, Dian Zheng, Hongbo Liu, Jingwen He, Bin Liu, Yu Qiao, Ziwei Liu
| Challenge: | Existing evaluations treat visual understanding and generation in isolation or overlook tasks that inherently couple them. |
| Approach: | They propose a benchmark that examines the bidirectional synergy between generation and understanding across eight reasoning-centric domains. |
| Outcome: | The proposed model systematically unfolds the bidirectional synergy between generation and understanding across eight reasoning-centric domains. |
Program Synthesis for Complex QA on Charts via Probabilistic Grammar Based Filtered Iterative Back-Translation (2023.findings-eacl)
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Shabbirhussain Bhaisaheb, Shubham Paliwal, Rajaswa Patil, Manasi Patwardhan, Lovekesh Vig, Gautam Shroff
| Challenge: | Current chart-based Question Answering approaches address structural, visual or simple data retrieval-type questions with fixed-vocabulary answers. |
| Approach: | They employ a neural semantic parser to transform NL questions into SQL programs . they use a probabilistic context-free grammar to generate NL queries from a schema . |
| Outcome: | The proposed approach achieves State-of-the-Art (SOTA) results on reasoning-based queries. |
Modeling Human-Like Cognition for Stance Detection: Integrating Intuitive Judgment and Analytical Reasoning (2026.acl-long)
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| Challenge: | Recent advances in large language models (LLMs) have revolutionized stance detection, enabling complex reasoning strategies such as chain-of-thought prompting. |
| Approach: | They propose Cognitive-Driven Stance Detection (CDSD) that integrates fast intuitive judgment and analytical reasoning enhanced by three key modules: attention-based cognitive alignment to compare system focus, uncertainty-aware belief update using Bayesian inference, and self-doubt-triggered counterfactual reasoning for re-evaluation under low consistency or high uncertainty. |
| Outcome: | The proposed method outperforms state-of-the-art methods on SEM16, P-Stance, and VAST. |
ReTAG: Reasoning Aware Table to Analytic Text Generation (2023.emnlp-main)
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| Challenge: | Table to text models generate descriptive summaries that repeat information contained within a table in sentences. |
| Approach: | They propose a table-aware table-to-text model that uses vector-quantization to infuse different types of analytical reasoning into the output. |
| Outcome: | The proposed model achieves 2.2%, 2.9% improvement on PARENT metric over state-of-the-art models. |
SAVOIR: Learning Social Savoir-Faire via Shapley-based Reward Attribution (2026.findings-acl)
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Xiachong Feng, Yi Jiang, Xiaocheng Feng, Deyi Yin, Libo Qin, Yangfan Ye, Lei Huang, Weitao Ma, Yuxuan Gu, Chonghan Qin, Bing Qin, Lingpeng Kong
| Challenge: | Existing approaches to improve social intelligence of AI systems employ retrospective attributions and lack theoretical grounding. |
| Approach: | They propose a framework that uses Shapley values to ensure fair credit distribution with axiomatic guarantees of efficiency, symmetry, and marginality. |
| Outcome: | The proposed framework matches or exceeds proprietary models including GPT-4o and Claude-3.5-Sonnet. |
HG-InsightLog: Context Prioritization and Reduction for Question Answering with Non-Natural Language Construct Log Data (2025.findings-acl)
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| Challenge: | Log files are crucial for monitoring, diagnostics, and root cause analysis in IT systems . their sheer volume makes manual analysis overwhelming and traditional methods are ineffective . |
| Approach: | They propose a framework that constructs a multi-entity temporal hypergraph using log attribute-value pairs as nodes and connects them with hyperedges. |
| Outcome: | The proposed framework is model-agnostic and training-free and scales with open-source LLMs. |