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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
E2E-AT: A Unified Framework for Tackling Uncertainty in Task-Aware End-to-End Learning
AAAI 2024
Socio-political Events of Conflict and Unrest: A Survey of Available Datasets
EACL 2024
One Self-Configurable Model to Solve Many Abstract Visual Reasoning Problems
AAAI 2024
Hypothesis, Verification, and Induction: Grounding Large Language Models with Self-Driven Skill Learning
AAAI 2024
Selene: Pioneering Automated Proof in Software Verification
ACL 2024
Stability Analysis of Switched Linear Systems with Neural Lyapunov Functions
AAAI 2024
Spatial-Logic-Aware Weakly Supervised Learning for Flood Mapping on Earth Imagery
AAAI 2024
Learning Neuro-Symbolic Abstractions for Robot Planning and Learning
AAAI 2024
Vector Poetics: Parallel Couplet Detection in Classical Chinese Poetry
EMNLP 2024
GProofT: A Multi-dimension Multi-round Fact Checking Framework Based on Claim Fact Extraction
EMNLP 2024
PizzaCommonSense: A Dataset for Commonsense Reasoning about Intermediate Steps in Cooking Recipes
EMNLP 2024
MDCR: A Dataset for Multi-Document Conditional Reasoning
EMNLP 2024
Communicating with Speakers and Listeners of Different Pragmatic Levels
EMNLP 2024
ControlMath: Controllable Data Generation Promotes Math Generalist Models
EMNLP 2024
Empowering Multi-step Reasoning across Languages via Program-Aided Language Models
EMNLP 2024
Explicit, Implicit, and Scattered: Revisiting Event Extraction to Capture Complex Arguments
EMNLP 2024
TheoremLlama: Transforming General-Purpose LLMs into Lean4 Experts
EMNLP 2024
What Are the Odds? Language Models Are Capable of Probabilistic Reasoning
EMNLP 2024
Dialogues Are Not Just Text: Modeling Cognition for Dialogue Coherence Evaluation
AAAI 2024
Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs
EMNLP 2024
Turning Dust into Gold: Distilling Complex Reasoning Capabilities from LLMs by Leveraging Negative Data
AAAI 2024
Belief Revision: The Adaptability of Large Language Models Reasoning
EMNLP 2024
Mastering Context-to-Label Representation Transformation for Event Causality Identification with Diffusion Models
AAAI 2024
The Logic of Doxastic Strategies
AAAI 2024
Large Language Models Are Neurosymbolic Reasoners
AAAI 2024
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