1 citations · 1 across the 4 of their papers we have counts for
4 papers
Understanding Knowledge Distillation in Post-Training: When It Helps and When It Fails
Xin Liu, Simin Ma, Shujian Liu +5
Large language models (LLMs) achieve strong performance across many tasks, but their high computational cost limits deployment in resource-constrained environments. Knowledge Disti…
Beyond Monolithic Rewards: A Hybrid and Multi-Aspect Reward Optimization for MLLM Alignment
Radha Gulhane, Sathish Reddy Indurthi
Aligning multimodal large language models (MLLMs) with human preferences often relies on single-signal, model-based reward methods. Such monolithic rewards often lack confidence ca…
Infusing Future Information into Monotonic Attention Through Language Models
Mohd Abbas Zaidi, Sathish Indurthi, Beomseok Lee +2
Simultaneous neural machine translation(SNMT) models start emitting the target sequence before they have processed the source sequence. The recent adaptive policies for SNMT use mo…
Small energy masking for improved neural network training for end-to-end speech recognition
Chanwoo Kim, Kwangyoun Kim, Sathish Reddy Indurthi
In this paper, we present a Small Energy Masking (SEM) algorithm, which masks inputs having values below a certain threshold. More specifically, a time-frequency bin is masked if t…