collaborators

10 papers

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.AI2026

Evaluation Cards: An Interpretive Layer for AI Evaluation Reporting

Avijit Ghosh, Anka Reuel, Jenny Chim +45

AI evaluation results are produced at scale but reported inconsistently across leaderboards, model cards, benchmark papers, and company blogs. The cost is interpretive: readers can…

cs.CL2026

Calibration of Structured Ignorance Certificates for Diagnosing Unknown Unknowns in Reasoning Models

Subramanyam Sahoo

Large language models frequently fail in a characteristic way: rather than acknowledging ignorance, they produce fluent but incorrect answers to questions that lie beyond their kno…

cs.CY2026

Memetic Capture: A Pluralistic Policy Framework for Governing AI-Driven Cultural Disempowerment

Subramanyam Sahoo

Culture is the most insidious vector of gradual human disempowerment by AI: unlike economic or political displacement, cultural displacement attacks the very preferences and values…

cond-mat.mtrl-sci2026

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Aritra Roy, Kevin Shen, Andrew MacBride +350

Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broa…

cs.LG2026

Calibration Collapse Under Sycophancy Fine-Tuning: How Reward Hacking Breaks Uncertainty Quantification in LLMs

Subramanyam Sahoo

Modern large language models (LLMs) are increasingly fine-tuned via reinforcement learning from human feedback (RLHF) or related reward optimisation schemes. While such procedures…