1 citations · 1 across the 9 of their papers we have counts for
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Compressing Many-Shots in In-Context Learning
Devvrit Khatri, Pranamya Kulkarni, Nilesh Gupta +9
Large Language Models (LLMs) have been shown to be able to learn different tasks without explicit finetuning when given many input-output examples / demonstrations through In-Conte…
Scalable In-context Ranking with Generative Models
Nilesh Gupta, Chong You, Srinadh Bhojanapalli +3
In-context Ranking (ICR) is an emerging paradigm for Information Retrieval (IR), which leverages contextual understanding of LLMs by directly incorporating the task description, ca…
LLM-guided Hierarchical Search for End-to-end Reasoning Intensive Retrieval
Nilesh Gupta, Wei-Cheng Chang, Ngot Bui +2
Search systems are increasingly used for reasoning-intensive queries, where what makes a document relevant requires understanding or reasoning over the query-document relation rath…