collaborators

7 papers

cs.SE2026

The Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes

Redacted by arXiv

This document consolidates publicly reported technical details about Metas Llama 4 model family. It summarizes (i) released variants (Scout and Maverick) and the broader herd conte…

cs.CL2025

Jailbreak-Zero: A Path to Pareto Optimal Red Teaming for Large Language Models

Kai Hu, Abhinav Aggarwal, Mehran Khodabandeh +6

This paper introduces Jailbreak-Zero, a novel red teaming methodology that shifts the paradigm of Large Language Model (LLM) safety evaluation from a constrained example-based appr…

cs.AI2025

GTAlign: Game-Theoretic Alignment of LLM Assistants for Social Welfare

Siqi Zhu, David Zhang, Pedro Cisneros-Velarde +1

Large Language Models (LLMs) have achieved remarkable progress in reasoning, yet sometimes produce responses that are suboptimal for users in tasks such as writing, information see…

cs.AI2025

The Challenge of Teaching Reasoning to LLMs Without RL or Distillation

Wei Du, Branislav Kisacanin, George Armstrong +22

Reasoning-capable language models achieve state-of-the-art performance in diverse complex tasks by generating long, explicit Chain-of-Thought (CoT) traces. While recent works show…

cs.CL2025

Domain Gating Ensemble Networks for AI-Generated Text Detection

Arihant Tripathi, Liam Dugan, Charis Gao +6

As state-of-the-art language models continue to improve, the need for robust detection of machine-generated text becomes increasingly critical. However, current state-of-the-art ma…

cs.LG2025

RL-finetuning LLMs from on- and off-policy data with a single algorithm

Yunhao Tang, Taco Cohen, David W. Zhang +2

We introduce a novel reinforcement learning algorithm (AGRO, for Any-Generation Reward Optimization) for fine-tuning large-language models. AGRO leverages the concept of generation…