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In-Context Learning

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Showing 1501–1550 of 2297 papers

TitleStatusHype
Speech-to-Speech Translation with Discrete-Unit-Based Style Transfer—0
SpiNNaker2: A Large-Scale Neuromorphic System for Event-Based and Asynchronous Machine Learning—0
Split and Rephrase with Large Language Models—0
Spoken Language Understanding on Unseen Tasks With In-Context Learning—0
SQL-Encoder: Improving NL2SQL In-Context Learning Through a Context-Aware Encoder—0
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)—0
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data—0
SSDM 2.0: Time-Accurate Speech Rich Transcription with Non-Fluencies—0
SSPA: Split-and-Synthesize Prompting with Gated Alignments for Multi-Label Image Recognition—0
Stabilized In-Context Learning with Pre-trained Language Models for Few Shot Dialogue State Tracking—0
StatBot.Swiss: Bilingual Open Data Exploration in Natural Language—0
State Soup: In-Context Skill Learning, Retrieval and Mixing—0
State-space models can learn in-context by gradient descent—0
Steering Large Language Models for Machine Translation with Finetuning and In-Context Learning—0
STEM-POM: Evaluating Language Models Math-Symbol Reasoning in Document Parsing—0
Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping—0
STEPS: A Benchmark for Order Reasoning in Sequential Tasks—0
StraGo: Harnessing Strategic Guidance for Prompt Optimization—0
Strategic Demonstration Selection for Improved Fairness in LLM In-Context Learning—0
Strategies for political-statement segmentation and labelling in unstructured text—0
StreamAdapter: Efficient Test Time Adaptation from Contextual Streams—0
Structured Prompting: Scaling In-Context Learning to 1,000 Examples—0
Studying LLM Performance on Closed- and Open-source Data—0
"Stupid robot, I want to speak to a human!" User Frustration Detection in Task-Oriented Dialog Systems—0
Style-Compress: An LLM-Based Prompt Compression Framework Considering Task-Specific Styles—0
Subject-driven Text-to-Image Generation via Apprenticeship Learning—0
Superiority of Multi-Head Attention in In-Context Linear Regression—0
Super-Prompting: Utilizing Model-Independent Contextual Data to Reduce Data Annotation Required in Visual Commonsense Tasks—0
Supervised Pretraining Can Learn In-Context Reinforcement Learning—0
Supporters and Skeptics: LLM-based Analysis of Engagement with Mental Health (Mis)Information Content on Video-sharing Platforms—0
Surprise Calibration for Better In-Context Learning—0
SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models—0
Symbol tuning improves in-context learning in language models—0
Synergizing In-context Learning with Hints for End-to-end Task-oriented Dialog Systems—0
SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design—0
Synthetic data enables context-aware bioacoustic sound event detection—0
Systematic Evaluation of Large Vision-Language Models for Surgical Artificial Intelligence—0
TabICL: A Tabular Foundation Model for In-Context Learning on Large Data—0
TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems—0
Tabular foundation model to detect empathy from visual cues—0
Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs—0
Tabular-TX: Theme-Explanation Structure-based Table Summarization via In-Context Learning—0
Take One Step at a Time to Know Incremental Utility of Demonstration: An Analysis on Reranking for Few-Shot In-Context Learning—0
TARGA: Targeted Synthetic Data Generation for Practical Reasoning over Structured Data—0
Targeted Distillation for Sentiment Analysis—0
Task Agnostic Architecture for Algorithm Induction via Implicit Composition—0
Task Generalization With AutoRegressive Compositional Structure: Can Learning From Tasks Generalize to ^T Tasks?—0
TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs—0
Tasks People Prompt: A Taxonomy of LLM Downstream Tasks in Software Verification and Falsification Approaches—0
Task Vectors in In-Context Learning: Emergence, Formation, and Benefit—0
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