36 citations · 36 across the 14 of their papers we have counts for
14 papers
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…
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…
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…
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…
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…
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…
A Unified Theory of Sparse Dictionary Learning in Mechanistic Interpretability: Piecewise Biconvexity and Spurious Minima
Yiming Tang, Harshvardhan Saini, Zhaoqian Yao +6
As AI models achieve remarkable capabilities across diverse domains, understanding what representations they learn and how they encode concepts has become increasingly important fo…
How does My Model Fail? Automatic Identification and Interpretation of Physical Plausibility Failure Modes with Matryoshka Transcoders
Yiming Tang, Abhijeet Sinha, Dianbo Liu
Although recent generative models are remarkably capable of producing instruction-following and realistic outputs, they remain prone to notable physical plausibility failures. Thou…
SPAGS: Sparse-View Articulated Object Reconstruction from Single State via Planar Gaussian Splatting
Di Wu, Liu Liu, Xueyu Yuan +5
Articulated objects are ubiquitous in daily environments, and their 3D reconstruction holds great significance across various fields. However, existing articulated object reconstru…
CXR-LanIC: Language-Grounded Interpretable Classifier for Chest X-Ray Diagnosis
Yiming Tang, Wenjia Zhong, Rushi Shah +1
Deep learning models have achieved remarkable accuracy in chest X-ray diagnosis, yet their widespread clinical adoption remains limited by the black-box nature of their predictions…
FML-bench: Benchmarking Machine Learning Agents for Scientific Research
Qiran Zou, Hou Hei Lam, Wenhao Zhao +7
Large language models (LLMs) have sparked growing interest in machine learning research agents that can autonomously propose ideas and conduct experiments. However, existing benchm…
Human-like Content Analysis for Generative AI with Language-Grounded Sparse Encoders
Yiming Tang, Arash Lagzian, Srinivas Anumasa +9
The rapid development of generative AI has transformed content creation, communication, and human development. However, this technology raises profound concerns in high-stakes doma…
M3PT: A Transformer for Multimodal, Multi-Party Social Signal Prediction with Person-aware Blockwise Attention
Yiming Tang, Abrar Anwar, Jesse Thomason
Understanding social signals in multi-party conversations is important for human-robot interaction and artificial social intelligence. Social signals include body pose, head pose,…
Multi-modal Transfer Learning for Grasping Transparent and Specular Objects
Thomas Weng, Amith Pallankize, Yimin Tang +2
State-of-the-art object grasping methods rely on depth sensing to plan robust grasps, but commercially available depth sensors fail to detect transparent and specular objects. To i…