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Methodology
← Core AI
Artificial Intelligence
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Core AI
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Reasoning
2595 directly classified papers
Papers per year
2003: 2
2006: 2
2007: 6
2008: 4
2009: 4
2010: 7
2011: 7
2012: 10
2013: 17
2014: 18
2015: 14
2016: 9
2017: 42
2018: 62
2019: 121
2020: 131
2021: 187
2022: 280
2023: 299
2024: 537
2025: 832
2026: 4
Papers
CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error Scenarios
EMNLP 2025
iVISPAR — An Interactive Visual-Spatial Reasoning Benchmark for VLMs
EMNLP 2025
Order Doesn’t Matter, But Reasoning Does: Training LLMs with Order-Centric Augmentation
EMNLP 2025
Frame First, Then Extract: A Frame-Semantic Reasoning Pipeline for Zero-Shot Relation Triplet Extraction
EMNLP 2025
TALON: A Multi-Agent Framework for Long-Table Exploration and Question Answering
EMNLP 2025
Investigating the interaction of linguistic and mathematical reasoning in language models using multilingual number puzzles
EMNLP 2025
SCRIBE: Structured Chain Reasoning for Interactive Behaviour Explanations using Tool Calling
EMNLP 2025
Structured Moral Reasoning in Language Models: A Value-Grounded Evaluation Framework
EMNLP 2025
VerIF: Verification Engineering for Reinforcement Learning in Instruction Following
EMNLP 2025
Improving Rule-based Reasoning in LLMs using Neurosymbolic Representations
EMNLP 2025
Are Language Models Consequentialist or Deontological Moral Reasoners?
EMNLP 2025
Is Cognition Consistent with Perception? Assessing and Mitigating Multimodal Knowledge Conflicts in Document Understanding
EMNLP 2025
AutoCT: Automating Interpretable Clinical Trial Prediction with LLM Agents
EMNLP 2025
ThinkTuning: Instilling Cognitive Reflections without Distillation
EMNLP 2025
ProReason: Multi-Modal Proactive Reasoning with Decoupled Eyesight and Wisdom
EMNLP 2025
All Roads Lead to Rome: Graph-Based Confidence Estimation for Large Language Model Reasoning
EMNLP 2025
Enhancing Logical Reasoning in Language Models via Symbolically-Guided Monte Carlo Process Supervision
EMNLP 2025
Reasoning under Uncertainty: Efficient LLM Inference via Unsupervised Confidence Dilution and Convergent Adaptive Sampling
EMNLP 2025
MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning
EMNLP 2025
DEBATE, TRAIN, EVOLVE: Self‐Evolution of Language Model Reasoning
EMNLP 2025
Threading the Needle: Reweaving Chain-of-Thought Reasoning to Explain Human Label Variation
EMNLP 2025
ImpliRet: Benchmarking the Implicit Fact Retrieval Challenge
EMNLP 2025
seqBench: A Tunable Benchmark to Quantify Sequential Reasoning Limits of LLMs
EMNLP 2025
SATBench: Benchmarking LLMs’ Logical Reasoning via Automated Puzzle Generation from SAT Formulas
EMNLP 2025
EoT: Evolution of Thoughts for Complex Reasoning Tasks
EMNLP 2025
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