1 citations · 1 across the 8 of their papers we have counts for
8 papers
Bibby AI: An Editor-Native Agentic Platform for Academic Research, Writing, and Publishing
Nilesh Jain
Academic output is produced across a fragmented toolchain: literature discovery in one application, reference management in another, writing in a LaTeX editor, formatting against v…
Bibby AI -- AI Latex Editor writing assistant for researchers vs Overleaf Alternative vs OpenAI Prism. (Bibby AI Latex Editor)
Nilesh jain, Rohit Yadav, Andrej Karpathy
Large language models are increasingly integrated into academic writing workflows; however, the most widely used \LaTeX\ editors remain AI-peripheral -- offering compilation and co…
Multi-LLM Thematic Analysis with Dual Reliability Metrics: Combining Cohen's Kappa and Semantic Similarity for Qualitative Research Validation
Nilesh Jain, Hyungil Suh, Seyi Adeyinka +2
Qualitative research faces a critical reliability challenge: traditional inter-rater agreement methods require multiple human coders, are time-intensive, and often yield moderate c…
TokenButler: Token Importance is Predictable
Yash Akhauri, Ahmed F AbouElhamayed, Yifei Gao +4
Large Language Models (LLMs) rely on the Key-Value (KV) Cache to store token history, enabling efficient decoding of tokens. As the KV-Cache grows, it becomes a major memory and co…
KVCrush: Key value cache size-reduction using similarity in head-behaviour
Gopi Krishna Jha, Sameh Gobriel, Liubov Talamanova +1
Key-value (KV) caching has emerged as a crucial optimization technique for accelerating inference in large language models (LLMs). By allowing the attention operation to scale line…
SparAMX: Accelerating Compressed LLMs Token Generation on AMX-powered CPUs
Ahmed F. AbouElhamayed, Jordan Dotzel, Yash Akhauri +6
Large language models have high compute, latency, and memory requirements. While specialized accelerators such as GPUs and TPUs typically run these workloads, CPUs are more widely…
Enhancing Data Integrity through Provenance Tracking in Semantic Web Frameworks
Nilesh Jain
This paper explores the integration of provenance tracking systems within the context of Semantic Web technologies to enhance data integrity in diverse operational environments. SU…
Post-Training Statistical Calibration for Higher Activation Sparsity
Vui Seng Chua, Yujie Pan, Nilesh Jain
We present Statistical Calibrated Activation Pruning (SCAP), a post-training activation pruning framework that (1) generalizes sparsification by input activations of Fully-Connecte…