papers

Publications (11)

cs.CV2025

Interpretable Face Anti-Spoofing: Enhancing Generalization with Multimodal Large Language Models

Guosheng Zhang, Keyao Wang, Haixiao Yue +5

Face Anti-Spoofing (FAS) is essential for ensuring the security and reliability of facial recognition systems. Most existing FAS methods are formulated as binary classification tas…

cs.CL2025

Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought

Tencent Hunyuan Team, Ao Liu, Botong Zhou +248

As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…

stat.ME2023

A Transparent and Nonlinear Method for Variable Selection

Keyao Wang, Huiwen Wang, Jichang Zhao +1

Variable selection is a procedure to attain the truly important predictors from inputs. Complex nonlinear dependencies and strong coupling pose great challenges for variable select…

cs.CV2026

Combating Visual Neglect and Semantic Drift in Large Multimodal Models for Enhanced Cross-Modal Retrieval

Guosheng Zhang, Linkai Liu, Keyao Wang +3

Despite significant progress in Unified Multimodal Retrieval (UMR) powered by Large Multimodal Models (LMMs), existing embedding methods primarily focus on sample-level objectives…

cs.CV2024

ALoRE: Efficient Visual Adaptation via Aggregating Low Rank Experts

Sinan Du, Guosheng Zhang, Keyao Wang +7

Parameter-efficient transfer learning (PETL) has become a promising paradigm for adapting large-scale vision foundation models to downstream tasks. Typical methods primarily levera…

cs.CV2020

Learning Generalized Spoof Cues for Face Anti-spoofing

Haocheng Feng, Zhibin Hong, Haixiao Yue +5

Many existing face anti-spoofing (FAS) methods focus on modeling the decision boundaries for some predefined spoof types. However, the diversity of the spoof samples including the…

math.OC2023

A Syntactic Adaptive Problem Solver Learning Landscape Structures for Scheduling in Clinical Laboratory

Keyao Wang, Bo Liu

This paper attempts to derive a mathematical formulation for real-practice clinical laboratory schedul-ing, and to present a syntactic adaptive problem solver by leveraging landsca…

cs.CV2021

ForgeryNet -- Face Forgery Analysis Challenge 2021: Methods and Results

Yinan He, Lu Sheng, Jing Shao +19

The rapid progress of photorealistic synthesis techniques has reached a critical point where the boundary between real and manipulated images starts to blur. Recently, a mega-scale…

cs.CV2022

Cyclically Disentangled Feature Translation for Face Anti-spoofing

Haixiao Yue, Keyao Wang, Guosheng Zhang +4

Current domain adaptation methods for face anti-spoofing leverage labeled source domain data and unlabeled target domain data to obtain a promising generalizable decision boundary.…

cs.CL2026

Diversity or Precision? A Deep Dive into Next Token Prediction

Haoyuan Wu, Hai Wang, Jiajia Wu +5

Recent advancements have shown that reinforcement learning (RL) can substantially improve the reasoning abilities of large language models (LLMs). The effectiveness of such RL trai…

cs.CV2026

From Intuition to Investigation: A Tool-Augmented Reasoning MLLM Framework for Generalizable Face Anti-Spoofing

Haoyuan Zhang, Keyao Wang, Guosheng Zhang +11

Face recognition remains vulnerable to presentation attacks, calling for robust Face Anti-Spoofing (FAS) solutions. Recent MLLM-based FAS methods reformulate the binary classificat…