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🏛️ The Computation & Language Crypt
cs.CL: Where Computation & Language papers rest without their code.
40064
Total Papers
26069
No Code
1086
Twilight
12909
Has Code
32.2%
Survival Rate
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The Structure of Relation Decoding Linear Operators in Large Language Models
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Hebrew Diacritics Restoration using Visual Representation
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A Multi-agent Large Language Model Framework to Automatically Assess Performance of a Clinical AI Triage Tool
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1+1>2: A Synergistic Sparse and Low-Rank Compression Method for Large Language Models
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OmniEduBench: A Comprehensive Chinese Benchmark for Evaluating Large Language Models in Education
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On the Role of Context for Discourse Relation Classification in Scientific Writing
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The Geometry of Dialogue: Graphing Language Models to Reveal Synergistic Teams for Multi-Agent Collaboration
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Distilling Multilingual Vision-Language Models: When Smaller Models Stay Multilingual
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Language Models Are Borrowing-Blind: A Multilingual Evaluation of Loanword Identification across 10 Languages
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Don't Let It Fade: Preserving Edits in Diffusion Language Models via Token Timestep Allocation
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RCScore: Quantifying Response Consistency in Large Language Models
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Similarity-Distance-Magnitude Language Models
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Artificial Intelligence-Enabled Analysis of Radiology Reports: Epidemiology and Consequences of Incidental Thyroid Findings
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PORTool: Tool-Use LLM Training with Rewarded Tree
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AttnCache: Accelerating Self-Attention Inference for LLM Prefill via Attention Cache
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NeuronMM: High-Performance Matrix Multiplication for LLM Inference on AWS Trainium
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Evaluating the Impact of LLM-Assisted Annotation in a Perspectivized Setting: the Case of FrameNet Annotation
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Decomposition-Enhanced Training for Post-Hoc Attributions In Language Models
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Completion $\neq$ Collaboration: Scaling Collaborative Effort with Agents
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The Limits of Obliviate: Evaluating Unlearning in LLMs via Stimulus-Knowledge Entanglement-Behavior Framework
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Knowledge Graph Analysis of Legal Understanding and Violations in LLMs
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Interpreting LLMs as Credit Risk Classifiers: Do Their Feature Explanations Align with Classical ML?
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