LLMs

Subasa - Adapting Language Models for Low-resourced Offensive Language Detection in Sinhala

ARTICLE: Annotator Reliability Through In-Context Learning

Using LLMs to identify high-quality human annotators by checking if their labels are consistent with AI predictions—helping build better training data while preserving diverse …

ProRefine: Inference-Time Prompt Refinement with Textual Feedback

ProRefine automatically improves AI prompts during inference by having one AI agent give feedback to refine another agent's prompts—boosting accuracy by 3-37% and helping smaller …

Blind Spot Navigation in Large Language Model Reasoning with Thought Space Explorer

Note Presenting at NeurIPS (Math-AI Workshop) Date: December 6, 2025 Time: Sat 3:30 p.m. - 4:15 p.m. Location: NeurIPS 2025 - Workshop Upper Level Ballroom 6A Session Type: Poster …

Harnessing Business and Media Insights with Large Language Models