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← Core AI
Artificial Intelligence
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Core AI
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Large Language Models
6,405 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
KB-Plugin: A Plug-and-play Framework for Large Language Models to Induce Programs over Low-resourced Knowledge Bases
EMNLP 2024
Verification and Refinement of Natural Language Explanations through LLM-Symbolic Theorem Proving
EMNLP 2024
Calibrating the Confidence of Large Language Models by Eliciting Fidelity
EMNLP 2024
CUTE: Measuring LLMs’ Understanding of Their Tokens
EMNLP 2024
SEER: Self-Aligned Evidence Extraction for Retrieval-Augmented Generation
EMNLP 2024
BC-Prover: Backward Chaining Prover for Formal Theorem Proving
EMNLP 2024
Word Alignment as Preference for Machine Translation
EMNLP 2024
SEEKR: Selective Attention-Guided Knowledge Retention for Continual Learning of Large Language Models
EMNLP 2024
Neuron-Level Knowledge Attribution in Large Language Models
EMNLP 2024
How do Large Language Models Learn In-Context? Query and Key Matrices of In-Context Heads are Two Towers for Metric Learning
EMNLP 2024
Interpreting Arithmetic Mechanism in Large Language Models through Comparative Neuron Analysis
EMNLP 2024
Pixology: Probing the Linguistic and Visual Capabilities of Pixel-based Language Models
EMNLP 2024
GoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theory
EMNLP 2024
QUIK: Towards End-to-end 4-Bit Inference on Generative Large Language Models
EMNLP 2024
Unsupervised Human Preference Learning
EMNLP 2024
Is Safer Better? The Impact of Guardrails on the Argumentative Strength of LLMs in Hate Speech Countering
EMNLP 2024
LLM4Decompile: Decompiling Binary Code with Large Language Models
EMNLP 2024
From Bottom to Top: Extending the Potential of Parameter Efficient Fine-Tuning
EMNLP 2024
CoTKR: Chain-of-Thought Enhanced Knowledge Rewriting for Complex Knowledge Graph Question Answering
EMNLP 2024
MTLS: Making Texts into Linguistic Symbols
EMNLP 2024
A User-Centric Multi-Intent Benchmark for Evaluating Large Language Models
EMNLP 2024
Decompose and Compare Consistency: Measuring VLMs’ Answer Reliability via Task-Decomposition Consistency Comparison
EMNLP 2024
Learn to Refuse: Making Large Language Models More Controllable and Reliable through Knowledge Scope Limitation and Refusal Mechanism
EMNLP 2024
VGBench: Evaluating Large Language Models on Vector Graphics Understanding and Generation
EMNLP 2024
Conditional and Modal Reasoning in Large Language Models
EMNLP 2024
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