2 citations · 7 across the 12 of their papers we have counts for
7 papers · 1 filter
LMK > CLS: Landmark Pooling for Dense Embeddings
Meet Doshi, Aashka Trivedi, Vishwajeet Kumar +5
Representation learning is central to many downstream tasks such as search, clustering, classification, and reranking. State-of-the-art sequence encoders typically collapse a varia…
Granite Embedding R2 Models
Parul Awasthy, Aashka Trivedi, Yulong Li +17
We introduce the Granite Embedding R2 models, a comprehensive family of high-performance English encoder-based embedding models engineered for enterprise-scale dense retrieval appl…
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…
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…
Muted: Multilingual Targeted Offensive Speech Identification and Visualization
Christoph Tillmann, Aashka Trivedi, Sara Rosenthal +4
Offensive language such as hate, abuse, and profanity (HAP) occurs in various content on the web. While previous work has mostly dealt with sentence level annotations, there have b…
A Comparative Analysis of Task-Agnostic Distillation Methods for Compressing Transformer Language Models
Takuma Udagawa, Aashka Trivedi, Michele Merler +1
Large language models have become a vital component in modern NLP, achieving state of the art performance in a variety of tasks. However, they are often inefficient for real-world…
Neural Architecture Search for Effective Teacher-Student Knowledge Transfer in Language Models
Aashka Trivedi, Takuma Udagawa, Michele Merler +3
Large pretrained language models have achieved state-of-the-art results on a variety of downstream tasks. Knowledge Distillation (KD) into a smaller student model addresses their i…