collaborators

10 papers

cs.CV2026

InfoDense: Density-Aware Regional Decisive Replay for Memory-Efficient Incremental Face Forgery Detection

Jikang Cheng, Hao Shen, Xueyi Zhang +4

The rapid evolution of face forgery techniques has introduced an increasing variety of manipulations. Incremental Face Forgery Detection (IFFD), which incrementally adds new forger…

cs.LG2026

Provable Affine Identifiability of Nonlinear CCA under Latent Distributional Priors

Zhiwei Han, Stefan Matthes, Hao Shen

In this work, we establish the sufficient conditions under which nonlinear Canonical Correlation Analysis (CCA) recovers ground-truth latent factors up to an affine transformation.…

cs.LG2026

Mechanistic Independence: A Principle for Identifiable Disentangled Representations

Stefan Matthes, Zhiwei Han, Hao Shen

Disentangled representations seek to recover latent factors of variation underlying observed data, yet their identifiability is still not fully understood. We introduce a unified f…

cs.AI2026

CSR-Bench: A Benchmark for Evaluating the Cross-modal Safety and Reliability of MLLMs

Yuxuan Liu, Yuntian Shi, Kun Wang +2

Multimodal large language models (MLLMs) enable interaction over both text and images, but their safety behavior can be driven by unimodal shortcuts instead of true joint intent un…

cs.LG2026

Ensuring Semantics in Weights of Implicit Neural Representations through the Implicit Function Theorem

Tianming Qiu, Christos Sonis, Hao Shen

Weight Space Learning (WSL), which frames neural network weights as a data modality, is an emerging field with potential for tasks like meta-learning or transfer learning. Particul…

cs.LG2026

An Analysis of Causal Effect Estimation using Outcome Invariant Data Augmentation

Uzair Akbar, Niki Kilbertus, Hao Shen +2

The technique of data augmentation (DA) is often used in machine learning for regularization purposes to better generalize under i.i.d. settings. In this work, we present a unifyin…