17 citations · 99 across the 66 of their papers we have counts for
80 papers
ForkGRPO: Efficient Exploration and Fine-Grained Credit Assignment for Diffusion Language Models
Zhaoyan Jia, Chengwei Zhou, Gourav Datta +1
Diffusion large language models (dLLMs) have advanced rapidly, yet strengthening their reasoning through reinforcement learning (RL) remains an open challenge. Any-order generation…
The Agent Knew: Internal States Forecast Unauthorized Actions and Stop Them, and the Lies That Follow
Arya Fayyazi, Mehdi Kamal, Massoud Pedram
Language-model agents sometimes act beyond their authorization and then misreport what they did. On CAPE-Bench, matched agent tasks in which one fact decides whether an action is a…
The Sharp Directions Are Against You: Curvature Analysis of Activation Steering
Seyedarmin Azizi, Arya Fayyazi, Parsa Razmara +3
Activation steering adds a vector to a language model's internal representations at inference time. It is a lightweight alternative to fine-tuning for behavioral control. The stand…
Stateless Stochastic Computing for Generative AI on Superconducting Logic: A Model-Hardware Co-Design
Mehdi Kamal, Massoud Pedram
Thermodynamic computing lets stochastic physical dynamics carry out a computation and reads out the result as a time average. Recently, thermodynamic computing has been demonstrate…
Running Fewer Loops Removes Refusal Behaviour in Recurrent-Depth Language Models
Seyedarmin Azizi, Erfan Baghaei Potraghloo, Arya Fayyazi +2
A recurrent-depth language model reuses one block of weights several times in a row. The number of repetitions, which we call loops, is chosen when the model runs, not when it is t…
Sharpen Without Search: On-Policy Distillation of Sequence-Level Power Distribution
Erfan Baghaei Potraghloo, Seyedarmin Azizi, Arya Fayyazi +4
A language model can give a correct answer more probability than any single incorrect answer and still usually sample an incorrect one, because the incorrect answers together hold…