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Language Modeling

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Showing 2551–2600 of 14182 papers

TitleStatusHype
CCpdf: Building a High Quality Corpus for Visually Rich Documents from Web Crawl DataCode1
Are Intermediate Layers and Labels Really Necessary? A General Language Model Distillation MethodCode1
Large Language Models as Realistic Microservice Trace GeneratorsCode1
CoditT5: Pretraining for Source Code and Natural Language EditingCode1
CoEdIT: Text Editing by Task-Specific Instruction TuningCode1
End-to-End Automatic Speech Recognition for GujaratiCode1
End-to-end Audio-visual Speech Recognition with ConformersCode1
CoFInAl: Enhancing Action Quality Assessment with Coarse-to-Fine Instruction AlignmentCode1
CCC-wav2vec 2.0: Clustering aided Cross Contrastive Self-supervised learning of speech representationsCode1
CriticEval: Evaluating Large Language Model as CriticCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question AnsweringCode1
Critic-Guided Decoding for Controlled Text GenerationCode1
Large language models are good medical coders, if provided with toolsCode1
CB-Conformer: Contextual biasing Conformer for biased word recognitionCode1
CogMG: Collaborative Augmentation Between Large Language Model and Knowledge GraphCode1
Large Language Model-Powered Smart Contract Vulnerability Detection: New PerspectivesCode1
CREAM: Consistency Regularized Self-Rewarding Language ModelsCode1
Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness?Code1
Cognitive Reframing of Negative Thoughts through Human-Language Model InteractionCode1
A Reference-less Quality Metric for Automatic Speech Recognition via Contrastive-Learning of a Multi-Language Model with Self-SupervisionCode1
CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language ModelCode1
Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context LearningCode1
AlephBERT:A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application WithCode1
Causal Structure Learning Supervised by Large Language ModelCode1
A Refer-and-Ground Multimodal Large Language Model for BiomedicineCode1
CoLA: Conditional Dropout and Language-driven Robust Dual-modal Salient Object DetectionCode1
Enhancing Dialogue Generation via Dynamic Graph Knowledge AggregationCode1
ModaVerse: Efficiently Transforming Modalities with LLMsCode1
Cold-start Active Learning through Self-supervised Language ModelingCode1
Cold-Start Data Selection for Few-shot Language Model Fine-tuning: A Prompt-Based Uncertainty Propagation ApproachCode1
Co-Learning: Code Learning for Multi-Agent Reinforcement Collaborative Framework with Conversational Natural Language InterfacesCode1
Are Emergent Abilities in Large Language Models just In-Context Learning?Code1
CausalLM is not optimal for in-context learningCode1
Crafting Large Language Models for Enhanced InterpretabilityCode1
Collaborative Large Language Model for Recommender SystemsCode1
Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!Code1
Collaborative Retrieval for Large Language Model-based Conversational Recommender SystemsCode1
Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic PuzzlesCode1
Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM CollaborationCode1
CrowdCLIP: Unsupervised Crowd Counting via Vision-Language ModelCode1
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and GenerationCode1
CPT: Efficient Deep Neural Network Training via Cyclic PrecisionCode1
Collective Constitutional AI: Aligning a Language Model with Public InputCode1
Detecting Hallucinations in Large Language Model Generation: A Token Probability ApproachCode1
CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal ControlCode1
Enhancing RL Safety with Counterfactual LLM ReasoningCode1
Large Language Model (LLM) as a System of Multiple Expert Agents: An Approach to solve the Abstraction and Reasoning Corpus (ARC) ChallengeCode1
Large Language Models Are Semi-Parametric Reinforcement Learning AgentsCode1
Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-trainingCode1
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