activity
20242026
most citedCRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

TailSieve: Partial-Rollout-Guided Tail Routing for LLM Rollouts

Tianqi Xu, Lu Lv, Haoyang Huang +15

Large-scale rollouts have become a core component of modern LLM systems, spanning reinforcement learning (RL) post-training, on-policy distillation (OPD), and sampling-heavy evalua…

cs.AI2026

OmniDelta: Skill-Driven Budget Allocation for Token Compression in OmniLLMs

Haoyang Huang, Wenjie Huang, Tianqi Xu +14

Emerging Omni-modal Large Language Models (OmniLLMs) enable unified understanding of text, audio, and video, but their long audio-video token sequences introduce substantial memory…

cs.CV2025

BOLT: Boost Large Vision-Language Model Without Training for Long-form Video Understanding

Shuming Liu, Chen Zhao, Tianqi Xu +1

Large video-language models (VLMs) have demonstrated promising progress in various video understanding tasks. However, their effectiveness in long-form video analysis is constraine…

cs.RO2024

EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents

Junting Chen, Checheng Yu, Xunzhe Zhou +7

Heterogeneous multi-robot systems (HMRS) have emerged as a powerful approach for tackling complex tasks that single robots cannot manage alone. Current large-language-model-based m…

cs.AI2024★ 1 cited

CRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents

Tianqi Xu, Linyao Chen, Dai-Jie Wu +13

The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites…