36 citations · 36 across the 14 of their papers we have counts for
7 papers · 1 filter
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,…