3 papers
cs.AI2026
Retrieval-Augmented Generation Must Move Beyond Factual Grounding to Represent Diverse Opinions
Aditya Agrawal, Alwarappan Nakkiran, Darshan Fofadiya +3
Retrieval-Augmented Generation (RAG) systems are built on an unexamined assumption - that queries have correct answers and retrieval should converge toward them. This position pape…
cs.CL2025
Idea-Gated Transformers: Enforcing Semantic Coherence via Differentiable Vocabulary Pruning
Darshan Fofadiya
Autoregressive Language Models (LLMs) trained on Next-Token Prediction (NTP) often suffer from Topic Drift where the generation wanders away from the initial prompt due to a relian…
cs.CL2021
Error Detection in Large-Scale Natural Language Understanding Systems Using Transformer Models
Rakesh Chada, Pradeep Natarajan, Darshan Fofadiya +1
Large-scale conversational assistants like Alexa, Siri, Cortana and Google Assistant process every utterance using multiple models for domain, intent and named entity recognition.…