3 papers
cs.LG2025
Sharing is Caring: Efficient LM Post-Training with Collective RL Experience Sharing
Jeffrey Amico, Gabriel Passamani Andrade, John Donaghy +12
Post-training language models (LMs) with reinforcement learning (RL) can enhance their complex reasoning capabilities without supervised fine-tuning, as demonstrated by DeepSeek-R1…
cs.LG2025
HDEE: Heterogeneous Domain Expert Ensemble
Oğuzhan Ersoy, Jari Kolehmainen, Gabriel Passamani Andrade
Training dense LLMs requires enormous amounts of data and centralized compute, which introduces fundamental bottlenecks and ever-growing costs for large models. Several studies aim…
eess.AS2024
Speech Recognition Rescoring with Large Speech-Text Foundation Models
Prashanth Gurunath Shivakumar, Jari Kolehmainen, Aditya Gourav +4
Large language models (LLM) have demonstrated the ability to understand human language by leveraging large amount of text data. Automatic speech recognition (ASR) systems are often…