activity
20242026
most citedGemma 2: Improving Open Language Models at a Practical Size

145 citations · 146 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2026

CT: Counterfactual Causal Reasoning for Sentiment Shifts in Social-Media Conversation Trees

S M Rafiuddin, Atriya Sen

Sentiment in social-media threads does not only vary across posts; it shifts as users react to claims, corrections, evidence, and hostility within a branching reply tree. We study…

cs.CL2026

HLE-Verified: A Systematic Verification and Structured Revision of Humanity's Last Exam

Weiqi Zhai, Zhihai Wang, Jinghang Wang +33

Humanity's Last Exam (HLE) has become a widely used benchmark for evaluating frontier large language models on challenging, multi-domain questions. However, community-led analyses…

cs.DC2025

Kant: An Efficient Unified Scheduling System for Large-Scale AI Clusters

Lingling Zeng, Gen Zhang, Jialin Peng +3

As AI cluster sizes continue to expand and the demand for large-language-model (LLM) training and inference workloads grows rapidly, traditional scheduling systems face significant…

cs.CL2025

Token Masking Improves Transformer-Based Text Classification

Xianglong Xu, John Bowen, Rojin Taheri

While transformer-based models achieve strong performance on text classification, we explore whether masking input tokens can further enhance their effectiveness. We propose token…

cs.CL2024★ 145 cited

Gemma 2: Improving Open Language Models at a Practical Size

Gemma Team, Morgane Riviere, Shreya Pathak +195

In this work, we introduce Gemma 2, a new addition to the Gemma family of lightweight, state-of-the-art open models, ranging in scale from 2 billion to 27 billion parameters. In th…

cs.DC2024★ 1 cited

P/D-Serve: Serving Disaggregated Large Language Model at Scale

Yibo Jin, Tao Wang, Huimin Lin +27

Serving disaggregated large language models (LLMs) over tens of thousands of xPU devices (GPUs or NPUs) with reliable performance faces multiple challenges. 1) Ignoring the diversi…