most citedScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2025

VerlTool: Towards Holistic Agentic Reinforcement Learning with Tool Use

Dongfu Jiang, Yi Lu, Zhuofeng Li +9

Reinforcement Learning with Verifiable Rewards (RLVR) has demonstrated success in enhancing LLM reasoning capabilities, but remains limited to single-turn interactions without tool…

cs.CL2025

BrowserAgent: Building Web Agents with Human-Inspired Web Browsing Actions

Tao Yu, Zhengbo Zhang, Zhiheng Lyu +8

Efficiently solving real-world problems with LLMs increasingly hinges on their ability to interact with dynamic web environments and autonomously acquire external information. Whil…

cs.CL2025

MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention

MiniMax, :, Aili Chen +125

We introduce MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model. MiniMax-M1 is powered by a hybrid Mixture-of-Experts (MoE) architecture combin…

cs.CL20251 cited

ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations

Yubo Wang, Xueguang Ma, Ping Nie +7

Academic writing requires both coherent text generation and precise citation of relevant literature. Although recent Retrieval-Augmented Generation (RAG) systems have significantly…

cs.CV2025

PixelWorld: How Far Are We from Perceiving Everything as Pixels?

Zhiheng Lyu, Xueguang Ma, Wenhu Chen

Recent agentic language models increasingly need to interact with real-world environments that contain tightly intertwined visual and textual information, often through raw camera…