collaborators

7 papers

cs.DS2026

Compact Path Representation in DAGs via Colored Edge Pebbling

Paola Bonizzoni, Alessio Conte, Gianluca Della Vedova +3

Compactly representing a variation graph is a core problem in computational pangenomics that is usually attacked with techniques that have been originated on texts and adapted to g…

cs.AI2026

Model or Harness? An Interaction-Centric Taxonomy for Localizing Agent Failures

Harsh Raj, Vipul Gupta, Anas Mahmoud +4

Existing evaluations often reduce agent failures to system-level outcomes, obscuring where the fault originated and which intervention would improve the agent system. This creates…

cs.AI2026

OpenThoughts-Agent: Data Recipes for Agentic Models

Negin Raoof, Richard Zhuang, Marianna Nezhurina +47

Agentic language models dramatically expand the applications of AI yet little is publicly known about how to curate training data for broadly capable agents. Existing open efforts…

cs.AI2026

Consistency as a Testable Property: Statistical Methods to Evaluate AI Agent Reliability

Harsh Raj, Niranjan Orkat, Suvrorup Mukherjee +3

This paper establishes a rigorous measurement science for AI agent reliability, providing a foundational framework for quantifying consistency under semantically preserving perturb…

cs.CL2025

Semantic Consistency for Assuring Reliability of Large Language Models

Harsh Raj, Vipul Gupta, Domenic Rosati +1

Large Language Models (LLMs) exhibit remarkable fluency and competence across various natural language tasks. However, recent research has highlighted their sensitivity to variatio…

cs.LG2025

Evaluating Defences against Unsafe Feedback in RLHF

Domenic Rosati, Giles Edkins, Harsh Raj +5

While there has been progress towards aligning Large Language Models (LLMs) with human values and ensuring safe behaviour at inference time, safety guards can easily be removed whe…