activity
20202026
collaborators

14 papers

math.FA2026

An unbounded convex set with the fixed point property for nonexpansive mappings

M. Japón, Javier Laguna-Ricart

We construct an equivalent norm on and a nonempty closed convex unbounded subset having the fixed point property for nonexpansive self-mappings. The ambien…

cs.AI2026

Self-Improvements in Modern Agentic Systems: A Survey

Zhe Ren, Yimeng Chen, Dandan Guo +9

Self-improving autonomous agents are moving from research prototypes to deployed systems. The primary goal is controllable evolution, or adaptation, from experience with minimal or…

cs.LG2026

FedFFT: Taming Client Drift in Federated SAM via Spectral Perturbation Filtering

Liyang Yuan, Yibo Yang, Dandan Guo

Federated Learning (FL) enables decentralized training without data sharing, but suffers from statistical heterogeneity across clients, leading to client drift, poor generalization…

cs.LG2026

GateMem: Benchmarking Memory Governance in Multi-Principal Shared-Memory Agents

Zhe Ren, Yibo Yang, Yimeng Chen +7

Memory benchmarks for LLM agents largely assume single-user settings, leaving shared assistants for hospitals, workplaces, campuses, and households understudied. In these deploymen…

cs.CL2026

MemSlides: A Hierarchical Memory Driven Agent Framework for Personalized Slide Generation with Multi-turn Local Revision

Ye Jin, Yangyang Xu, Jun Zhu +1

Personalized presentation generation requires more than conditioning on a current prompt or template: agents must preserve stable user preferences across tasks, retain newly introd…

cs.AI2026

Mental-R1: Aligning LLM Reasoning for Mental Health Assessment

Xin Wang, Boyan Gao, Yibo Yang +1

Mental health problems such as anxiety, depression, and suicide remain urgent global challenges, where timely and accurate assessment is critical for effective intervention. Recent…

cs.CL2026

H2HMem: A Multimodal Memory Benchmark for Agents in Human-Human Interactions

Shiping Zhu, Yibo Yang, Zhengyang Wang +3

Large language model agents are increasingly deployed in human-human interaction settings, such as meeting assistants and clinical documentation systems, where they must observe co…

cs.CL2026

Detecting AI-Generated Content on Social Media with Multi-modal Language Models

Chenyang Yang, Shen Yan, Yibo Yang +13

Generative AI has enabled the creation of photorealistic images and videos that are increasingly disseminated on social media, often used for spam, misinformation, manipulation, an…

cs.LG2026

Safeguarding LLM Fine-tuning via Push-Pull Distributional Alignment

Haozhong Wang, Zhuo Li, Yibo Yang +3

The inherent safety alignment of Large Language Models (LLMs) is prone to erosion during fine-tuning, even when using seemingly innocuous datasets. While existing defenses attempt…

cs.CL2026

PDR: A Plug-and-Play Positional Decay Framework for LLM Pre-training Data Detection

Jinhan Liu, Yibo Yang, Ruiying Lu +4

Detecting pre-training data in Large Language Models (LLMs) is crucial for auditing data privacy and copyright compliance, yet it remains challenging in black-box, zero-shot settin…

cs.LG2025

Deep Neural Network Calibration by Reducing Classifier Shift with Stochastic Masking

Jiani Ni, He Zhao, Yibo Yang +1

In recent years, deep neural networks (DNNs) have shown competitive results in many fields. Despite this success, they often suffer from poor calibration, especially in safety-crit…

cs.CL2025

MCPVerse: An Expansive, Real-World Benchmark for Agentic Tool Use

Fei Lei, Yibo Yang, Wenxiu Sun +1

Large Language Models (LLMs) are evolving from text generators into reasoning agents. This transition makes their ability to use external tools a critical capability. However, eval…

cs.CV2025

Instruction-Oriented Preference Alignment for Enhancing Multi-Modal Comprehension Capability of MLLMs

Zitian Wang, Yue Liao, Kang Rong +3

Preference alignment has emerged as an effective strategy to enhance the performance of Multimodal Large Language Models (MLLMs) following supervised fine-tuning. While existing pr…

cs.LG2020

Lifted Hybrid Variational Inference

Yuqiao Chen, Yibo Yang, Sriraam Natarajan +1

A variety of lifted inference algorithms, which exploit model symmetry to reduce computational cost, have been proposed to render inference tractable in probabilistic relational mo…