51 citations · 61 across the 9 of their papers we have counts for
10 papers
Flash-dLLM: IO-Aware KV Caching and Parallel Decoding for Fast, Memory-Efficient Diffusion LLMs
Quan Nguyen-Tri, Mukul Ranjan, Zhiqiang Shen
Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to autoregressive LLMs by enabling non-autoregressive text generation. However, their pract…
Operation-Guided Progressive Human-to-AI Text Transformation Benchmark for Multi-Granularity AI-Text Detection
Sondos Mahmoud Bsharat, Jiacheng Liu, Xiaohan Zhao +9
As AI writing assistants become increasingly integrated into real-world drafting and revision workflows, many documents are no longer purely human-written or AI-generated, but inst…
Search-Time Contamination in Deep Research Agents: Measuring Performance Inflation in Public Benchmark Evaluation
Yongjie Wang, Xinyue Zhang, Kunhong Yao +4
Public benchmarks enable fair and reproducible evaluation of LLM reasoning, but they become fragile for deep research agents that actively search the web during inference. Such age…
Prompting Test-Time Scaling Is A Strong LLM Reasoning Data Augmentation
Sondos Mahmoud Bsharat, Zhiqiang Shen
Large language models (LLMs) have demonstrated impressive reasoning capabilities when provided with chain-of-thought exemplars, but curating large reasoning datasets remains labori…
Attention Is All You Need for KV Cache in Diffusion LLMs
Quan Nguyen-Tri, Mukul Ranjan, Zhiqiang Shen
This work studies how to adaptively recompute key-value (KV) caches for diffusion large language models (DLMs) to maximize prediction accuracy while minimizing decoding latency. Pr…
Time Blindness: Why Video-Language Models Can't See What Humans Can?
Ujjwal Upadhyay, Mukul Ranjan, Zhiqiang Shen +1
Recent advances in vision-language models (VLMs) have made impressive strides in understanding spatio-temporal relationships in videos. However, when spatial information is obscure…
Mobile-MMLU: A Mobile Intelligence Language Understanding Benchmark
Sondos Mahmoud Bsharat, Mukul Ranjan, Aidar Myrzakhan +6
Rapid advancements in large language models (LLMs) have increased interest in deploying them on mobile devices for on-device AI applications. Mobile users interact differently with…
KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding
Ahmed Heakl, Abdullah Sohail, Mukul Ranjan +7
With the growing adoption of Retrieval-Augmented Generation (RAG) in document processing, robust text recognition has become increasingly critical for knowledge extraction. While O…
Open-LLM-Leaderboard: From Multi-choice to Open-style Questions for LLMs Evaluation, Benchmark, and Arena
Aidar Myrzakhan, Sondos Mahmoud Bsharat, Zhiqiang Shen
Multiple-choice questions (MCQ) are frequently used to assess large language models (LLMs). Typically, an LLM is given a question and selects the answer deemed most probable after…
Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4
Sondos Mahmoud Bsharat, Aidar Myrzakhan, Zhiqiang Shen
This paper introduces 26 guiding principles designed to streamline the process of querying and prompting large language models. Our goal is to simplify the underlying concepts of f…