12 citations · 23 across the 15 of their papers we have counts for
10 papers · 1 filter
SkillForge: Evolving Verifiable Skills for Reinforcement Learning Agents
Shidong Yang, Ziyu Ma, Tongwen Huang +5
Large language model (LLM) agents are trained with reinforcement learning (RL) for complex decision-making tasks. However, most RL-trained agents remain episodic and cannot accumul…
LongHorizon-Harness: Advancing Long-Horizon Agents for Real-World Tasks
Ziyu Ma, Hailang Huang, Shun Zou +5
Large language model (LLM) agents increasingly undertake long-horizon tasks that require sustained reasoning, tool use, and revision across many interdependent steps. However, exis…
MMShopBench: A Real-Log Benchmark for Multimodal, Multi-Turn Shopping Agents
Zeying Hao, Hao Guo, Mengtao Xu +5
Online shoppers increasingly turn to AI shopping assistants, using images and multi-turn dialogue to express and refine product needs that are difficult to articulate in text alone…
Towards High-Resolution Visual Perception via Hierarchical Entity Exploration
Ziyu Ma, Shidong Yang, Yuxiang Ji +5
High-resolution (HR) image perception remains a key challenge in multimodal large language models (MLLMs), as fine-grained details are often lost when the image is processed as a w…
Towards Memory-Efficient Autoregressive Video Generation via Instance-Specific Parametric Absorption
Xiaomeng Fu, Jia Li, Yiming Hu +5
Autoregressive (AR) streaming models have emerged as a powerful paradigm for long video generation. However, the linearly growing Key-Value (KV) cache poses a significant bottlenec…
BlockPilot: Instance-Adaptive Policy Learning for Diffusion-based Speculative Decoding
Hao Zhang, Yiming Hu, Yong Wang +3
Speculative decoding accelerates inference by using a lightweight draft model to generate candidate tokens in parallel, and are then verified by the target model, enabling lossless…
SkillChain: Closing the Loop on Skill Evolution for Image-Based E-Commerce AI Assistants
Yimin Hu, Mengtao Xu, Hao Guo +3
Image-based AI assistants are now deployed at production scale on e-commerce platforms, where a single uploaded image can trigger fundamentally different user intents: product sear…
CoEvolve: Training LLM Agents via Agent-Data Mutual Evolution
Shidong Yang, Ziyu Ma, Tongwen Huang +3
Reinforcement learning for LLM agents is typically conducted on a static data distribution, which fails to adapt to the agent's evolving behavior and leads to poor coverage of comp…
SkillClaw: Let Skills Evolve Collectively with Agentic Evolver
Ziyu Ma, Shidong Yang, Yuxiang Ji +5
Large language model (LLM) agents such as OpenClaw rely on reusable skills to perform complex tasks, yet these skills remain largely static after deployment. As a result, similar w…
Thinking with Map: Reinforced Parallel Map-Augmented Agent for Geolocalization
Yuxiang Ji, Yong Wang, Ziyu Ma +6
The image geolocalization task aims to predict the location where an image was taken anywhere on Earth using visual clues. Existing large vision-language model (LVLM) approaches le…