3 papers
cs.CV2026
Improving Reasoning in Vision-Language Models via Perception Verified Self-Training
Sourabh Sharma, Sonam Gupta, Sadbhawna
Achieving human-like reasoning in Vision-Language Models (VLMs) remains a long-standing challenge. Recent approaches leverage Chain-of-Thought (CoT) rationales generated by human a…
cs.CL2025
Systematic Knowledge Injection into Large Language Models via Diverse Augmentation for Domain-Specific RAG
Kushagra Bhushan, Yatin Nandwani, Dinesh Khandelwal +4
Retrieval-Augmented Generation (RAG) has emerged as a prominent method for incorporating domain knowledge into Large Language Models (LLMs). While RAG enhances response relevance b…
cs.CL2025
Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models
Sonam Gupta, Yatin Nandwani, Asaf Yehudai +3
Fine-tuning Large Language Models (LLMs) on specific datasets is a common practice to improve performance on target tasks. However, this performance gain often leads to overfitting…