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In-Context Learning

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Showing 1401–1450 of 2297 papers

TitleStatusHype
RealGeneral: Unifying Visual Generation via Temporal In-Context Learning with Video Models—0
RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios—0
Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models—0
Reasoning before Responding: Integrating Commonsense-based Causality Explanation for Empathetic Response Generation—0
Reasoning with Large Language Models, a Survey—0
Recall, Retrieve and Reason: Towards Better In-Context Relation Extraction—0
Recording for Eyes, Not Echoing to Ears: Contextualized Spoken-to-Written Conversion of ASR Transcripts—0
Re-examining learning linear functions in context—0
Refashioning Emotion Recognition Modelling: The Advent of Generalised Large Models—0
REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context in New Environments—0
Reinforcing Question Answering Agents with Minimalist Policy Gradient Optimization—0
Relational Programming with Foundation Models—0
Repetition Neurons: How Do Language Models Produce Repetitions?—0
Repetitions are not all alike: distinct mechanisms sustain repetition in language models—0
Resona: Improving Context Copying in Linear Recurrence Models with Retrieval—0
Rethinking Graph Structure Learning in the Era of LLMs—0
Retrieval-Augmented Chain-of-Thought in Semi-structured Domains—0
Retrieval-Augmented Code Generation for Universal Information Extraction—0
Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft—0
Retrieval Augmented End-to-End Spoken Dialog Models—0
Retrieval-augmented in-context learning for multimodal large language models in disease classification—0
Retrieval-Augmented Multimodal Language Modeling—0
Retrieval-Enhanced Named Entity Recognition—0
Retrieval & Fine-Tuning for In-Context Tabular Models—0
Retrieved In-Context Principles from Previous Mistakes—0
Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison—0
Revisiting Chain-of-Thought Prompting: Zero-shot Can Be Stronger than Few-shot—0
Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models—0
Revisiting In-Context Learning with Long Context Language Models—0
Revisiting the Practical Effectiveness of Constituency Parse Extraction from Pre-trained Language Models—0
Rich Semantic Knowledge Enhanced Large Language Models for Few-shot Chinese Spell Checking—0
RL2: Reinforce Large Language Model to Assist Safe Reinforcement Learning for Energy Management of Active Distribution Networks—0
Direct Preference Optimization for LLM-Enhanced Recommendation Systems—0
Robust Neural Processes for Noisy Data—0
Table Integration in Data Lakes Unleashed: Pairwise Integrability Judgment, Integrable Set Discovery, and Multi-Tuple Conflict Resolution—0
RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation—0
RuAG: Learned-rule-augmented Generation for Large Language Models—0
RVISA: Reasoning and Verification for Implicit Sentiment Analysis—0
R+X: Retrieval and Execution from Everyday Human Videos—0
SADL: An Effective In-Context Learning Method for Compositional Visual QA—0
Random Policy Enables In-Context Reinforcement Learning within Trust Horizons—0
SafePowerGraph-LLM: Novel Power Grid Graph Embedding and Optimization with Large Language Models—0
SAFE-SQL: Self-Augmented In-Context Learning with Fine-grained Example Selection for Text-to-SQL—0
SALM: Speech-augmented Language Model with In-context Learning for Speech Recognition and Translation—0
Satisfactory Medical Consultation based on Terminology-Enhanced Information Retrieval and Emotional In-Context Learning—0
Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models—0
Scaling Context, Not Parameters: Training a Compact 7B Language Model for Efficient Long-Context Processing—0
Scaling In-Context Demonstrations with Structured Attention—0
Scaling sparse feature circuit finding for in-context learning—0
Scenarios and Approaches for Situated Natural Language Explanations—0
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