Large Language Model Reasoning

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NoisyCausal: A Benchmark for Evaluating Causal Reasoning Under Structured Noise
May 5, 2026Zhi Xu, Yun FuLarge Language Model Reasoning Causal Graph
Temporal Reasoning Is Not the Bottleneck: A Probabilistic Inconsistency Framework for Neuro-Symbolic QA
May 5, 2026Tran Quang LiemNeuro-Symbolic Framework Reasoning Failures
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Correct Is Not Enough: Training Reasoning Planners with Executor-Grounded Rewards
May 5, 2026Tianyang Han, Hengyu Shi, Junjie Hu +3Reasoning Traces Planning Methods
Say the Mission, Execute the Swarm: Agent-Enhanced LLM Reasoning in the Web-of-Drones
May 5, 2026Andrea Iannoli, Lorenzo Gigli, Luca Sciullo +2Unmanned Aerial Vehicle Swarms Swarms
Rose-SQL: Role-State Evolution Guided Structured Reasoning for Multi-Turn Text-to-SQL
May 5, 2026Le Zhou, Feng Yao, Fengcai Qiao +3Text-To-Sql Sql
Echo-LoRA: Parameter-Efficient Fine-Tuning via Cross-Layer Representation Injection
May 5, 2026Yihang Peng, Peng Jin, Jie Gong +4Parameter-Efficient Fine-Tuning Reasoning Benchmark
MHPR: Multidimensional Human Perception and Reasoning Benchmark for Large Vision-Languate Models
May 5, 2026Kangkang Wang, Qinting Jiang, Wanping Zhang +2Multimodal Reasoning Benchmarks Large Vision Language Models
FinSTaR: Towards Financial Reasoning with Time Series Reasoning Models
May 5, 2026Seunghan Lee, Jun Seo, Jaehoon Lee +7Large Reasoning Models Time Series
ReasonAudio: A Benchmark for Evaluating Reasoning Beyond Matching in Text-Audio Retrieval
May 5, 2026Honglei Zhang, Yuting Chen, Chenpeng Hu +2Audio Reasoning Benchmark
RAG over Thinking Traces Can Improve Reasoning Tasks
May 5, 2026Negar Arabzadeh, Wenjie Ma, Sewon Min +1Reasoning Traces
DGPO: Distribution Guided Policy Optimization for Fine Grained Credit Assignment
May 5, 2026Hongbo Jin, Rongpeng Zhu, Zhongjing Du +4Multi-Objective Policy Optimization Credit Assignment
When to Think, When to Speak: Learning Disclosure Policies for LLM Reasoning
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Revisiting the Travel Planning Capabilities of Large Language Models
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Evaluating Prompting and Execution-Based Methods for Deterministic Computation in LLMs
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Evaluating Reasoning Models for Queries with Presuppositions
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Visual Latents Know More Than They Say: Unsilencing Latent Reasoning in MLLMs
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May 4, 2026Berk Çiçek, Mert K. Er, Ozgur S. OguzContact-Rich Manipulation Manipulation
Strategy-Aware Optimization Modeling with Reasoning LLMs
May 4, 2026Ruiqing Zhao, Fengzhi Li, Yuan Zuo +5Llm-Based Optimization Modeling Large Language Model Reasoning
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May 4, 2026Qiaohong Zhang, Weihao Ye, Jialong Chen +7Agentic Benchmarks Data Lakes
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HeavySkill: Heavy Thinking as the Inner Skill in Agentic Harness
May 4, 2026Jianing Wang, Linsen Guo, Zhengyu Chen +8Agentic Reasoning Agent Harness
Verifiable Counterfactual Supervision for Process Reward Models
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Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding
May 4, 2026Taewon Yun, Jisu Shin, Jeonghwan Choi +2Reasoning Trajectory Low-Quality Data
Towards Understanding Specification Gaming in Reasoning Models
May 4, 2026Kei Nishimura-Gasparian, Robert McCarthy, David LindnerLarge Reasoning Models Agentic Reasoning
Break the Block: Dynamic-size Reasoning Blocks for Diffusion Large Language Models via Monotonic Entropy Descent with Reinforcement Learning
May 4, 2026Yan Jiang, Ruihong Qiu, Zi HuangDiffusion Language Models Large Language Model Reasoning
Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning
May 3, 2026Arash Ahmadi, Sarah Sharif, Yaser +1Large Language Model Reasoning External Reward Models
HALO: Hybrid Adaptive Latent Reasoning for Language Models
May 3, 2026Micah ZhangSample-Wise 2D Refinement Efficient Latent Reasoning
StressEval: Failure-Driven Dynamic Benchmarking for Knowledge-Intensive Reasoning in Large Language Models
May 3, 2026Yongrui Chen, Yangyang Ma, Xiaoying Huang +4Reasoning Benchmark Stress Testing
Chart-FR1: Visual Focus-Driven Fine-Grained Reasoning on Dense Charts
May 3, 2026Hongkun Pan, Yuwei Wu, Wanyi Hong +8Chart Multimodal Reasoning
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May 3, 2026Nikolaos Giarelis, Charalampos Mastrokostas, Nikos KaracapilidisMultilingual Large Language Models Large Language
Spatiotemporal Hidden-State Dynamics as a Signature of Internal Reasoning in Large Language Models
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Only Say What You Know: Calibration-Aware Generation for Long-Form Factuality
May 3, 2026Wen Luo, Guangyue Peng, Liang Wang +7Facts Long-Form Generation
The Reasoning Trap: An Information-Theoretic Bound on Closed-System Multi-Step LLM Reasoning
May 3, 2026Kwan Soo ShinMulti-Agent Debate Debate
Act2See: Emergent Active Visual Perception for Video Reasoning
May 3, 2026Martin Q. Ma, Yuxiao Qu, Aditya Agrawal +4Visual Reasoning Visual Perception
Multi-Agent Reasoning Improves Compute Efficiency: Pareto-Optimal Test-Time Scaling
May 2, 2026Florian Valentin Wunderlich, Lars Benedikt Kaesberg, Jan Philip Wahle +2Test-Time Scaling Multi-Agent Reasoning
Grounding Multi-Hop Reasoning in Structural Causal Models via Group Relative Policy Optimization
May 2, 2026Yunhan Bu, Quan Zhang, Huaping Zhang +9Multi-Hop Reasoning Structural Causal Model
ReMedi: Reasoner for Medical Clinical Prediction
May 2, 2026Yushi Cao, Yiming Chen, Hongchao Jiang +2Clinical Prediction Electronic Health Records
Rethinking Explanations: Formalizing Contrast in Description Logics
May 2, 2026Yasir Mahmood, Arnab Sharma, Axel-Cyrille Ngonga Ngomo +1Counterfactual Explanation Contrastive
Reasoning emerges from constrained inference manifolds in large language models
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Beyond Perceptual Shortcuts: Causal-Inspired Debiasing Optimization for Generalizable Video Reasoning in Lightweight MLLMs
May 2, 2026Jingze Wu, Quan Zhang, Hongfei Suo +2Video Understanding Visual Reasoning
GR-Ben: A General Reasoning Benchmark for Evaluating Process Reward Models
May 2, 2026Zhouhao Sun, Xuan Zhang, Xiao Ding +10Reasoning Benchmark Reliable Medical Process-Level Reward Model Evaluation Framework
LLMs Should Not Yet Be Credited with Decision Explanation
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To Use AI as Dice of Possibilities with Timing Computation
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When Less is Enough: Efficient Inference via Collaborative Reasoning
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When LLMs Stop Following Steps: A Diagnostic Study of Procedural Execution in Language Models
May 1, 2026Sailesh Panda, Pritam Kadasi, Abhishek Upperwal +1Large Language Model Performance Reasoning Benchmark
KARA: Efficient Reasoning LLM Serving via Sliding-Window KV Cache Compression
May 1, 2026Shen Han, Yuyang Wu, Junpu Yu +1Key-Value Cache Compression Large Language Model Compression
Beyond Benchmarks: MathArena as an Evaluation Platform for Mathematics with LLMs
May 1, 2026Jasper Dekoninck, Nikola Jovanović, Tim Gehrunger +4Mathematical Reasoning Mathematics
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May 1, 2026Zihan Ding, Ziyuan Yang, Yi ZhangMemes Hate Speech
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May 1, 2026Jinkun Liu, Haohan Chi, Lingfeng Zhang +6Long-Horizon Planning Visual Reasoning
ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning
May 1, 2026Zihan Lin, Xiaohan Wang, Jie Cao +6Reinforcement Learning With Verifiable Reward Large Language Model Reasoning
Assert, don't describe: Linguistic features that shift LLM reasoning about animal welfare
Apr 30, 2026Jasmine Brazilek, Harper DunnLinguistics Large Language Model Reasoning
Retrieval-Augmented Reasoning for Chartered Accountancy
Apr 30, 2026Jatin Gupta, Akhil Sharma, Saransh Singhania +1Large Reasoning Models Regulation
State Stream Transformer (SST) V2: Parallel Training of Nonlinear Recurrence for Latent Space Reasoning
Apr 30, 2026Thea AvissEfficient Latent Reasoning Parallel
RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasoners
Apr 30, 2026Jugal Gajjar, Kamalasankari SubramaniakuppusamyLarge Language Model Reasoning Reasoning Traces
LaST-R1: Reinforcing Robotic Manipulation via Adaptive Physical Latent Reasoning
Apr 30, 2026Hao Chen, Jiaming Liu, Zhonghao Yan +10Efficient Latent Reasoning
Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning
Apr 30, 2026Shijin Gong, Kai Ye, Jin Zhu +3Large Language Model Reasoning Policy Gradient

May 5, 2026 · cs.CLJ/K move · Enter open · S save

NoisyCausal: A Benchmark for Evaluating Causal Reasoning Under Structured Noise

Zhi Xu, Yun Fu

Northeastern University

Causal reasoning in natural language requires identifying relevant variables, understanding their interactions, and reasoning about effects and interventions, often under noisy or ambiguous conditions. While large language models (LLMs) exhibit strong general reasoning abilities, they struggle to disentangle correlation from causation, particularly when observations are partially incorrect or irrelevant information is present. In this work, we introduce NoisyCausal, a new benchmark designed to evaluate causal reasoning under structured noise. Each instance is generated from a ground-truth causal graph and contextualized with a natural language scenario by injecting controllable forms of noise, such as irrelevant distractors, value perturbations, confounding, and partial observability. Moreover, we propose a modular reasoning framework that combines LLMs with explicit causal structure to address these challenges. Our method prompts the LLM to extract variables, construct a causal graph from context, and then reformulates the reasoning task as a structured prompt grounded in this graph. Rather than relying on statistical patterns alone, the LLM is guided by symbolic structure, enabling more interpretable and robust inference. Experimental results show that our method significantly outperforms standard prompting and reasoning baselines on NoisyCausal. Furthermore, it generalizes well to external benchmarks such as Cladder without task-specific tuning. Our findings highlight the importance of combining causal abstractions with language-driven reasoning to achieve faithful and robust causal understanding in LLMs.

Large Language Model Reasoning Causal Graph Causal Reasoning Causal Inferences Noisy Data

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