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cs.LG2025
PathFinder: MCTS and LLM Feedback-based Path Selection for Multi-Hop Question Answering
Durga Prasad Maram, Kalpa Gunaratna, Vijay Srinivasan +2
Multi-hop question answering is a challenging task in which language models must reason over multiple steps to reach the correct answer. With the help of Large Language Models and…
cs.LG2020
Generalized Reinforcement Meta Learning for Few-Shot Optimization
Raviteja Anantha, Stephen Pulman, Srinivas Chappidi
We present a generic and flexible Reinforcement Learning (RL) based meta-learning framework for the problem of few-shot learning. During training, it learns the best optimization a…
cs.LG2020
Learning to Rank Intents in Voice Assistants
Raviteja Anantha, Srinivas Chappidi, William Dawoodi
Voice Assistants aim to fulfill user requests by choosing the best intent from multiple options generated by its Automated Speech Recognition and Natural Language Understanding sub…