activity
20222026
most citedRobust Semi-Supervised Learning in Open Environments

13 citations · 16 across the 12 of their papers we have counts for

collaborators

16 papers

cs.LG2026

Stabilizing Recurrent Dynamics for Test-Time Scalable Latent Reasoning in Looped Language Models

Xiao-Wen Yang, Ziyu Han, Xi-Hua Zhang +4

Looped Language Models (LoopLMs) enable efficient latent reasoning through depth recurrence, yet exhibit unreliable test-time scaling behavior: performance often peaks at a certain…

cs.AI2026

Revisiting the Travel Planning Capabilities of Large Language Models

Bo-Wen Zhang, Jin Ye, Peng-Yu Hua +4

Travel planning serves as a critical task for long-horizon reasoning, exposing significant deficits in LLMs. However, existing benchmarks and evaluations primarily assess final pla…

cs.AI2026

Lifting Traces to Logic: Programmatic Skill Induction with Neuro-Symbolic Learning for Long-Horizon Agentic Tasks

Jie-Jing Shao, Haiyan Yin, Yueming Lyu +5

Foundation model-driven agents often struggle with long-horizon planning due to the transient nature of purely prompting-based reasoning. While existing skill induction methods mit…

cs.LG2026

Hindsight Credit Assignment for Long-Horizon LLM Agents

Hui-Ze Tan, Xiao-Wen Yang, Hao Chen +7

Large Language Model (LLM) agents often face significant credit assignment challenges in long-horizon, multi-step tasks due to sparse rewards. Existing value-free methods, such as…

cs.SD2025

Pianist Transformer: Towards Expressive Piano Performance Rendering via Scalable Self-Supervised Pre-Training

Hong-Jie You, Jie-Jing Shao, Xiao-Wen Yang +3

Existing methods for expressive music performance rendering, a conditional generation task that aims to generate a human-like performance from a symbolic score, rely on supervised…

cs.AI2025

Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models

Xiao-Wen Yang, Jie-Jing Shao, Lan-Zhe Guo +5

Large Language Models (LLMs) have shown promising results across various tasks, yet their reasoning capabilities remain a fundamental challenge. Developing AI systems with strong r…