Neel Dani — accepted AI-conference papers

2026

AutoSP: Unlocking Long-Context LLM Training Via Compiler-Based Sequence Parallelism

Ahan Gupta, Zhihao Wang, Neel Dani, Masahiro Tanaka, Olatunji Ruwase, Minjia Zhang

ICLR 2026poster

Large-language-models (LLMs) demonstrate enormous utility in long-context tasks which require processing prompts that consist of tens to hundreds of thousands of tokens. However, existing LLM training libraries do not provide easy to use abstractions to optimize for long-context training, instead fo…

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2025

MiniKV: Pushing the Limits of 2-Bit KV Cache via Compression and System Co-Design for Efficient Long Context Inference

Akshat Sharma, Hangliang Ding, Jianping Li, Neel Dani, Minjia Zhang

ACL 2025finding

State-of-the-art 2-bit KV cache quantization techniques achieve excellent results in accelerating LLM inference while retaining accuracy on long context tasks. However, further pushing the compression ratio fails to deliver performance gains. In this work, we revisit these approaches by considering,…

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