6 citations · 7 across the 23 of their papers we have counts for
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cs.CL2026
OThink-SRR1: Search, Refine and Reasoning with Reinforced Learning for Large Language Models
Haijian Liang, Zenghao Niu, Junjie Wu +3
Retrieval-Augmented Generation (RAG) expands the knowledge of Large Language Models (LLMs), yet current static retrieval methods struggle with complex, multi-hop problems. While re…
cs.CL2026
TSEmbed: Unlocking Task Scaling in Universal Multimodal Embeddings
Yebo Wu, Feng Liu, Ziwei Xie +4
Despite the exceptional reasoning capabilities of Multimodal Large Language Models (MLLMs), their adaptation into universal embedding models is significantly impeded by task confli…
cs.CL2025
TaskCraft: Automated Generation of Agentic Tasks
Dingfeng Shi, Jingyi Cao, Qianben Chen +14
Agentic tasks, which require multi-step problem solving with autonomy, tool use, and adaptive reasoning, are becoming increasingly central to the advancement of NLP and AI. However…