collaborators

8 papers

cs.RO2026

ForesightSafety-VLA: A Unified Diagnostic Safety Benchmark for Vision-Language-Action Models

Mingyang Lyu, Yinqian Sun, Yiyang Jia +5

In embodied intelligence, safety is a prerequisite for reliable robot deployment in the physical world. Current vision-language-action (VLA) models continue to advance toward gener…

cs.LG2026

When Autoregressive Consistency Hurts Safety Alignment

Bochen Lyu, Yiyang Jia, Xiaohao Cai +1

Safety alignment in large language models (LLMs) is fragile in part because it is often shallow: fine-tuning mainly reshapes the model's behavior near the first few output tokens.…

cs.LG2026

Transformers with RL or SFT Provably Learn Sparse Boolean Functions, But Differently

Bochen Lyu, Yiyang Jia, Xiaohao Cai +1

Transformers can acquire Chain-of-Thought (CoT) capabilities to solve reasoning tasks via fine-tuning. Reinforcement learning (RL) and supervised fine-tuning (SFT) are two primary…

cs.NE2025

Self-Motivated Growing Neural Network for Adaptive Architecture via Local Structural Plasticity

Yiyang Jia, Chengxu Zhou

Control policies are often implemented with fixed-capacity multilayer perceptrons trained by backpropagation, which require architecture selection in advance and cannot adapt their…

cs.AI2025

A Categorical Analysis of Large Language Models and Why LLMs Circumvent the Symbol Grounding Problem

Luciano Floridi, Yiyang Jia, Fernando Tohmé

This paper presents a formal, categorical framework for analysing how humans and large language models (LLMs) transform content into truth-evaluated propositions about a state spac…

q-bio.MN2025

Modeling GRNs with a Probabilistic Categorical Framework

Yiyang Jia, Zheng Wei, Zheng Yang +1

Understanding the complex and stochastic nature of Gene Regulatory Networks (GRNs) remains a central challenge in systems biology. Existing modeling paradigms often struggle to eff…