2 citations · 7 across the 12 of their papers we have counts for
4 papers · 1 filter
INDUS: Effective and Efficient Language Models for Scientific Applications
Bishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka +33
Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs tr…
Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations
Swapnaja Achintalwar, Adriana Alvarado Garcia, Ateret Anaby-Tavor +35
Large language models (LLMs) are susceptible to a variety of risks, from non-faithful output to biased and toxic generations. Due to several limiting factors surrounding LLMs (trai…
An Empirical Investigation into the Effect of Parameter Choices in Knowledge Distillation
Md Arafat Sultan, Aashka Trivedi, Parul Awasthy +1
We present a large-scale empirical study of how choices of configuration parameters affect performance in knowledge distillation (KD). An example of such a KD parameter is the meas…
Efficient Models for the Detection of Hate, Abuse and Profanity
Christoph Tillmann, Aashka Trivedi, Bishwaranjan Bhattacharjee
Large Language Models (LLMs) are the cornerstone for many Natural Language Processing (NLP) tasks like sentiment analysis, document classification, named entity recognition, questi…