Papers by Akshat Sharma
MiniKV: Pushing the Limits of 2-Bit KV Cache via Compression and System Co-Design for Efficient Long Context Inference (2025.findings-acl)
Copied to clipboard
| Challenge: | State-of-the-art 2-bit KV cache quantization methods achieve excellent results in accelerating LLM inference while retaining accuracy on long context tasks. |
| Approach: | They propose a method based on 2-bit KV cache quantization with adaptive KV policies that retain LLM accuracy with only a subset of KV states. |
| Outcome: | The proposed method outperforms state-of-the-art methods on a wide range of long context tasks while retaining accuracy. |
IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoning (2024.acl-long)
Copied to clipboard
| Challenge: | Legal systems worldwide struggle with exponentially growing legal cases in various courts. |
| Approach: | They propose a benchmark for Indian legal text understanding and reasoning task that includes domain-specific tasks that address different aspects of the legal system. |
| Outcome: | The proposed benchmark for Indian legal text understanding and reasoning aims to address the gap between models and the ground truth. |
U-CREAT: Unsupervised Case Retrieval using Events extrAcTion (2023.acl-long)
Copied to clipboard
| Challenge: | Prior Case Retrieval (PCR) is about automatically citing relevant prior legal cases in a given query case. |
| Approach: | They propose a new benchmark for prior case retrieval based on a legal query case . they propose an unsupervised retrieval method-based pipeline U-CREAT . |
| Outcome: | The proposed method significantly improves performance and makes retrieval faster compared to BM25. |