activity
20202026
most citedMulti-modal Transfer Learning for Grasping Transparent and Specular Objects

36 citations · 36 across the 14 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

cs.LG2026

Capsule Lens: Locating and Tracking Concept Geometry in Model Representations

Yiming Tang, Harshvardhan Saini, Samyak Jha +3

Understanding how concepts are encoded in the internal representations of machine learning models is a central problem in mechanistic interpretability, essential both for the scien…

cs.CV2026

Emergent Hierarchical Monosemantic Neurons from the Group-Contrastive Forward-Forward Algorithm

Yiming Tang, Qinglin Qi, Zhaoqian Yao +2

Mechanistic interpretability has made significant strides in understanding neural network representations, with sparse dictionary learning (SDL) methods, most prominently sparse au…

cs.CV2026

When Language Overwrites Vision: Over-Alignment and Geometric Debiasing in Vision-Language Models

Harshvardhan Saini, Samyak Jha, Yiming Tang +1

Vision-Language Models (VLMs) increasingly power high-stakes applications, from medical imaging to autonomous systems, yet they routinely hallucinate, confidently describing conten…

cs.LG2026

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics

Qiran Zou, Hou Hei Lam, Wenhao Zhao +11

AI research agents accelerate ML research by automating hypothesis generation, experimentation, and empirical refinement. Existing agent strategies range from greedy hill-climbing…

cs.CE2026

Navigating heterogeneous protein landscapes through geometry-aware smoothing

Srinivas Anumasa, Barath Chandran, Tingting Chen +15

The evolutionary fitness landscape of biological molecules is extremely sparse and heterogeneous, with functional sequences forming isolated dense ``islands'' within a vast combina…

cs.LG2026

Bridging Mechanistic Interpretability and Prompt Engineering with Gradient Ascent for Interpretable Persona Control

Harshvardhan Saini, Yiming Tang, Dianbo Liu

Controlling emergent behavioral personas (e.g., sycophancy, hallucination) in Large Language Models (LLMs) is critical for AI safety, yet remains a persistent challenge. Existing s…