7 papers · 1 filter
Approximating Human Preferences Using a Multi-Judge Learned System
Eitán Sprejer, Fernando Avalos, Augusto Bernardi +3
Aligning LLM-based judges with human preferences is a significant challenge, as they are difficult to calibrate and often suffer from rubric sensitivity, bias, and instability. Ove…
Position: Require Frontier AI Labs To Release Small "Analog" Models
Shriyash Upadhyay, Chaithanya Bandi, Narmeen Oozeer +1
Recent proposals for regulating frontier AI models have sparked concerns about the cost of safety regulation, and most such regulations have been shelved due to the safety-innovati…
Breaking the Mirror: Activation-Based Mitigation of Self-Preference in LLM Evaluators
Dani Roytburg, Matthew Bozoukov, Matthew Nguyen +3
Large language models (LLMs) increasingly serve as automated evaluators, yet they suffer from "self-preference bias": a tendency to favor their own outputs over those of other mode…
Distribution-Aware Feature Selection for SAEs
Narmeen Oozeer, Nirmalendu Prakash, Michael Lan +2
Sparse autoencoders (SAEs) decompose neural activations into interpretable features. A widely adopted variant, the TopK SAE, reconstructs each token from its K most active latents.…
Beyond Monoliths: Expert Orchestration for More Capable, Democratic, and Safe Language Models
Philip Quirke, Narmeen Oozeer, Chaithanya Bandi +8
This position paper argues that the prevailing trajectory toward ever larger, more expensive generalist foundation models controlled by a handful of companies limits innovation and…
Beyond Linear Steering: Unified Multi-Attribute Control for Language Models
Narmeen Oozeer, Luke Marks, Shreyans Jain +2
Controlling multiple behavioral attributes in large language models (LLMs) at inference time is a challenging problem due to interference between attributes and the limitations of…
Activation Space Interventions Can Be Transferred Between Large Language Models
Narmeen Oozeer, Dhruv Nathawani, Nirmalendu Prakash +3
The study of representation universality in AI models reveals growing convergence across domains, modalities, and architectures. However, the practical applications of representati…