collaborators

5 papers

cs.AI2026

Intertemporal Preference Steering in Qwen3 via Contrastive Activation Addition

Michal Mráz, Michal Mráz, Justin Shenk

We study linear representations of temporal horizon in the large language model Qwen3-32B and use them to change the model's time-related preferences, recommendations, and capabili…

cs.AI2026

The Knowing-Saying Gap: When Probes See Errors that Confidence Misses

Jyotin Goel, Ipshita Bandyopadhyay, Justin Shenk

Linear probes detect corrupted context in language models with near-perfect accuracy, yet this does not translate into reliable failure prediction. The result is a dissociation wit…

cs.LG2026

Temporal Preference Concepts and their Functions in a Large Language Model

Ian Rios-Sialer, Shantanu Darveshi, Shuai Jiang +4

Large Language Models (LLMs) are increasingly being deployed to make decisions that require trading off near-term gains against long-term consequences, yet little is known about ho…

cs.CL2026

Creative Collision: Directorial Persona Steering and Competition in Large Language Models

Subramanyam Sahoo, Justin Shenk

Activation steering has emerged as a powerful tool for shaping the behaviour of large language models at inference time, yet most prior work injects a \emph{single} semantic direct…

cs.CR2026

LinuxArena: A Control Setting for AI Agents in Live Production Software Environments

Tyler Tracy, Ram Potham, Nick Kuhn +31

We introduce LinuxArena, a control setting in which agents operate directly on live, multi-service production environments. LinuxArena contains 20 environments, 1,671 main tasks re…