52 citations · 56 across the 4 of their papers we have counts for
4 papers
Crafting Interpretable Embeddings by Asking LLMs Questions
Vinamra Benara, Chandan Singh, John X. Morris +4
Large language models (LLMs) have rapidly improved text embeddings for a growing array of natural-language processing tasks. However, their opaqueness and proliferation into scient…
RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture
Angels Balaguer, Vinamra Benara, Renato Luiz de Freitas Cunha +13
There are two common ways in which developers are incorporating proprietary and domain-specific data when building applications of Large Language Models (LLMs): Retrieval-Augmented…
NumS: Scalable Array Programming for the Cloud
Melih Elibol, Vinamra Benara, Samyu Yagati +4
Scientists increasingly rely on Python tools to perform scalable distributed memory array operations using rich, NumPy-like expressions. However, many of these tools rely on dynami…
Synthesizing Power and Area Efficient Image Processing Pipelines on FPGAs using Customized Bit-widths
Vinamra Benara, Ziaul Choudhury, Suresh Purini +1
High-level synthesis (HLS) has received significant attention in recent years, improving programmability for FPGAs. PolyMage is a domain-specific language (DSL) for image processin…