activity
20242026
collaborators

8 papers

cs.LG2026

PTGPO: Prefix Tree Group Policy Optimization

Ruolin Chen, Yang Li, Jihang Wang +4

Training language agents on long-horizon interactive tasks is challenging because sparse terminal rewards provide weak credit signals for intermediate actions. Existing group-based…

cs.AI2026

ForesightSafety Bench: A Frontier Risk Evaluation and Governance Framework towards Safe AI

Haibo Tong, Feifei Zhao, Linghao Feng +18

Rapidly evolving AI exhibits increasingly strong autonomy and goal-directed capabilities, accompanied by derivative systemic risks that are more unpredictable, difficult to control…

cs.AI2026

CogToM: A Comprehensive Theory of Mind Benchmark inspired by Human Cognition for Large Language Models

Haibo Tong, Zeyang Yue, Feifei Zhao +6

Whether Large Language Models (LLMs) truly possess human-like Theory of Mind (ToM) capabilities has garnered increasing attention. However, existing benchmarks remain largely restr…

cs.LG2025

Towards Reliable Evaluation of Adversarial Robustness for Spiking Neural Networks

Jihang Wang, Dongcheng Zhao, Ruolin Chen +2

Spiking Neural Networks (SNNs) utilize spike-based activations to mimic the brain's energy-efficient information processing. However, the binary and discontinuous nature of spike a…

cs.LG2025

Reinforcement Fine-Tuning of Flow-Matching Policies for Vision-Language-Action Models

Mingyang Lyu, Yinqian Sun, Erliang Lin +4

Vision-Language-Action (VLA) models such as OpenVLA, Octo, and have shown strong generalization by leveraging large-scale demonstrations, yet their performance is still funda…

cs.AI2025

SafeMind: Benchmarking and Mitigating Safety Risks in Embodied LLM Agents

Ruolin Chen, Yinqian Sun, Jihang Wang +3

Embodied agents powered by large language models (LLMs) inherit advanced planning capabilities; however, their direct interaction with the physical world exposes them to safety vul…

cs.LG2025

Boosting the Robustness-Accuracy Trade-off of SNNs by Robust Temporal Self-Ensemble

Jihang Wang, Dongcheng Zhao, Ruolin Chen +2

Spiking Neural Networks (SNNs) offer a promising direction for energy-efficient and brain-inspired computing, yet their vulnerability to adversarial perturbations remains poorly un…

cs.CY2024

A.I. In All The Wrong Places

Marc Böhlen, Ruolin Chen, Xiaoxu Dong +4

This text describes experiences gained across a two-year test period during which two generations of Generative Artificial Intelligence (A.I.) systems were incorporated into an int…