collaborators

7 papers

cs.AI2026

Business Arena: Benchmarking LLM Agents in a Realistic Marketplace

Yijun Pan, Yukun Lian, Kunyu Shi +5

Running a business is a challenging form of intelligent work. Operators must infer opportunities from partial signals, commit capital under uncertainty, adapt to delayed outcomes i…

cs.CV2026

Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models

Shilin Yan, Jintao Tong, Hongwei Xue +6

The advent of agentic multimodal models has empowered systems to actively interact with external environments. However, current agents suffer from a profound meta-cognitive deficit…

cs.CV2026

MM-CondChain: A Programmatically Verified Benchmark for Visually Grounded Deep Compositional Reasoning

Haozhan Shen, Shilin Yan, Hongwei Xue +5

Multimodal Large Language Models (MLLMs) are increasingly used to carry out visual workflows such as navigating GUIs, where the next step depends on verified visual compositional c…

cs.CV2026

Beyond Scattered Acceptance: Fast and Coherent Inference for DLMs via Longest Stable Prefixes

Pengxiang Li, Joey Tsai, Hongwei Xue +2

Diffusion Language Models (DLMs) promise highly parallel text generation, yet their practical inference speed is often bottlenecked by suboptimal decoding schedulers. Standard appr…

cs.CV2026

SwimBird: Eliciting Switchable Reasoning Mode in Hybrid Autoregressive MLLMs

Jintao Tong, Shilin Yan, Hongwei Xue +5

Multimodal Large Language Models (MLLMs) have made remarkable progress in multimodal perception and reasoning by bridging vision and language. However, most existing MLLMs perform…

cs.AI2026

You Only Forward Once: An Efficient Compositional Judging Paradigm

Tianlong Zhang, Hongwei Xue, Shilin Yan +4

Multimodal large language models (MLLMs) show strong potential as judges. However, existing approaches face a fundamental trade-off: adapting MLLMs to output a single score misalig…