1 citations · 1 across the 13 of their papers we have counts for
13 papers
AI Agents and the Future of VIS
Chen Zhu-Tian, Nam Wook Kim, Saeed Boorboor +4
Recent advances in agents (i.e., autonomous, goal-driven AI systems that iteratively observe, act, and learn from their environments) offer a fundamentally different approach from…
Riemannian-Manifold Steering: Geometry-Aware Generative Autoencoders for Label-Free Steering
Narmeen Oozeer, Shivam Raval, Philip Quirke +4
Steering a language model - intervening on its internal activations to change downstream behaviour - has recently expanded beyond linear interpolation to nonlinear methods such as…
H-Probes: Extracting Hierarchical Structures From Latent Representations of Language Models
Cutter Dawes, Aryan Sharma, Angelos Ioannis Lagos +1
Representing and navigating hierarchy is a fundamental primitive of reasoning. Large language models have demonstrated proficiency in a wide variety of tasks requiring hierarchical…
Intersectional Sycophancy: How Perceived User Demographics Shape False Validation in Large Language Models
Benjamin Maltbie, Shivam Raval
Large language models exhibit sycophantic tendencies, but whether this behavior varies systematically with perceived user demographics is underexplored. Inspired by intersectionali…
Geometry-Aware CLIP Retrieval via Local Cross-Modal Alignment and Steering
Nirmalendu Prakash, Narmeen Fatimah Oozeer, Xin Su +8
CLIP retrieval is typically framed as a pointwise similarity problem in a shared embedding space. While CLIP achieves strong global cross-modal alignment, many retrieval failures a…
Dissociating Decodability and Causal Use in Bracket-Sequence Transformers
Aryan Sharma, Cutter Dawes, Shivam Raval
When trained on tasks requiring an understanding of hierarchical structure, transformers have been found to represent this hierarchy in distinct ways: in the geometry of the residu…
Curveball Steering: The Right Direction To Steer Isn't Always Linear
Shivam Raval, Hae Jin Song, Linlin Wu +4
Activation steering is a widely used approach for controlling large language model (LLM) behavior by intervening on internal representations. Existing methods largely rely on the L…
Narrow Fine-Tuning Erodes Safety Alignment in Vision-Language Agents
Idhant Gulati, Shivam Raval
Lifelong multimodal agents must continuously adapt to new tasks through post-training, but this creates a fundamental tension between acquiring capabilities and preserving safety a…
MoE Lens -- An Expert Is All You Need
Marmik Chaudhari, Idhant Gulati, Nishkal Hundia +2
Mixture of Experts (MoE) models enable parameter-efficient scaling through sparse expert activations, yet optimizing their inference and memory costs remains challenging due to lim…
DreamReader: An Interpretability Toolkit for Text-to-Image Models
Nirmalendu Prakash, Narmeen Oozeer, Michael Lan +6
Despite the rapid adoption of text-to-image (T2I) diffusion models, causal and representation-level analysis remains fragmented and largely limited to isolated probing techniques.…
Spectral Superposition: A Theory of Feature Geometry
Georgi Ivanov, Narmeen Oozeer, Shivam Raval +3
Neural networks represent more features than they have dimensions via superposition, forcing features to share representational space. Current methods decompose activations into sp…
Measure what Matters: Psychometric Evaluation of AI with Situational Judgment Tests
Alexandra Yost, Shreyans Jain, Shivam Raval +6
Persona conditioning is widely used to steer large language model (LLM) behavior, but it is unclear whether it induces stable behavioral structure or superficial variation. We prop…
Linear probes rely on textual evidence: Results from leakage mitigation studies in language models
Gerard Boxo, Aman Neelappa, Shivam Raval
White-box monitors are a popular technique for detecting potentially harmful behaviours in language models. While they perform well in general, their effectiveness in detecting tex…