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Methodology
← Core AI
Artificial Intelligence
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Core AI
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Large Language Models
6405 directly classified papers
Papers per year
2007: 3
2017: 2
2018: 3
2019: 10
2020: 49
2021: 53
2022: 188
2023: 558
2024: 1910
2025: 3619
2026: 10
Papers
SIMBA UQ: Similarity-Based Aggregation for Uncertainty Quantification in Large Language Models
EMNLP 2025
S*: Test Time Scaling for Code Generation
EMNLP 2025
Language Models Can Easily Learn to Reason from Demonstrations
EMNLP 2025
Benchmarking and Improving LLM Robustness for Personalized Generation
EMNLP 2025
Hallucination Detection in Structured Query Generation via LLM Self-Debating
EMNLP 2025
Not All Options Are Created Equal: Textual Option Weighting for Token-Efficient LLM-Based Knowledge Tracing
EMNLP 2025
TTPA: Token-level Tool-use Preference Alignment Training Framework with Fine-grained Evaluation
EMNLP 2025
Avoiding Knowledge Edit Skipping in Multi-hop Question Answering with Guided Decomposition
EMNLP 2025
Bridging the Creativity Understanding Gap: Small-Scale Human Alignment Enables Expert-Level Humor Ranking in LLMs
EMNLP 2025
Exploring Deductive and Inductive Reasoning Capabilities of Large Language Models in Procedural Planning
EMNLP 2025
KELE: A Multi-Agent Framework for Structured Socratic Teaching with Large Language Models
EMNLP 2025
OkraLong: A Flexible Retrieval-Augmented Framework for Long-Text Question Answering
EMNLP 2025
VerifiAgent: a Unified Verification Agent in Language Model Reasoning
EMNLP 2025
DrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains
EMNLP 2025
Understanding the Language Model to Solve the Symbolic Multi-Step Reasoning Problem from the Perspective of Buffer Mechanism
EMNLP 2025
TwT: Thinking without Tokens by Habitual Reasoning Distillation with Multi-Teachers’ Guidance
EMNLP 2025
When Instructions Multiply: Measuring and Estimating LLM Capabilities of Multiple Instructions Following
EMNLP 2025
SeaPO: Strategic Error Amplification for Robust Preference Optimization of Large Language Models
EMNLP 2025
Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging
EMNLP 2025
Self-Ensemble: Mitigating Confidence Distortion for Large Language Models
EMNLP 2025
Annotation-Efficient Language Model Alignment via Diverse and Representative Response Texts
EMNLP 2025
DecisionFlow: Advancing Large Language Model as Principled Decision Maker
EMNLP 2025
M-Ped: Multi-Prompt Ensemble Decoding for Large Language Models
EMNLP 2025
Butterfly Effects in Toolchains: A Comprehensive Analysis of Failed Parameter Filling in LLM Tool-Agent Systems
EMNLP 2025
EnDive: A Cross-Dialect Benchmark for Fairness and Performance in Large Language Models
EMNLP 2025
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