activity
20242026
most citedFlexSP: Accelerating Large Language Model Training via Flexible Sequence Parallelism

2 citations · 3 across the 7 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.LG2025

Virtual Width Networks

Seed, Baisheng Li, Banggu Wu +115

We introduce Virtual Width Networks (VWN), a framework that delivers the benefits of wider representations without incurring the quadratic cost of increasing the hidden size. VWN d…

cs.AI2025

Game-TARS: Pretrained Foundation Models for Scalable Generalist Multimodal Game Agents

Zihao Wang, Xujing Li, Yining Ye +24

We present Game-TARS, a generalist game agent trained with a unified, scalable action space anchored to human-aligned native keyboard-mouse inputs. Unlike API- or GUI-based approac…

cs.AI2025

UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning

Haoming Wang, Haoyang Zou, Huatong Song +109

The development of autonomous agents for graphical user interfaces (GUIs) presents major challenges in artificial intelligence. While recent advances in native agent models have sh…

cs.CV2025★ 1 cited

Seed1.5-VL Technical Report

Dong Guo, Faming Wu, Feida Zhu +194

We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…

cs.DC2025

OrchMLLM: Orchestrate Multimodal Data with Batch Post-Balancing to Accelerate Multimodal Large Language Model Training

Yijie Zheng, Bangjun Xiao, Lei Shi +7

Multimodal large language models (MLLMs), such as GPT-4o, are garnering significant attention. During the exploration of MLLM training, we identified Modality Composition Incoheren…