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MMR1: Enhancing Multimodal Reasoning with Variance-Aware Sampling and Open Resources
Large multimodal reasoning models have achieved rapid progress, but their advancement is constrained by two major limitations: the …
Sicong Leng, Jing Wang, Jiaxi Li, Hao Zhang, Zhiqiang Hu, Boqiang Zhang, Yuming Jiang, Hang Zhang, Xin Li, Lidong Bing, Deli Zhao, Wei Lu, Yu Rong, Aixin Sun, Shijian Lu
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MMR1: Enhancing Multimodal Reasoning with Variance-Aware Sampling and Open Resources
AMAZe: A Multi-Agent Zero-shot Index Advisor for Relational Databases
Index recommendation is one of the most important problems in database management system (DBMS) optimization. Given queries and certain …
Zhaodonghui Li, Haitao Yuan, Jiachen Shi, Hao Zhang, Yu Rong, Gao Cong
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AMAZe: A Multi-Agent Zero-shot Index Advisor for Relational Databases
VL-Cogito: Progressive Curriculum Reinforcement Learning for Advanced Multimodal Reasoning
Reinforcement learning has proven its effectiveness in enhancing the reasoning capabilities of large language models. Recent research …
Ruifeng Yuan, Chenghao Xiao, Sicong Leng, Jianyu Wang, Long Li, Weiwen Xu, Hou Pong Chan, Deli Zhao, Tingyang Xu, Zhongyu Wei, Hao Zhang, Yu Rong
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VL-Cogito: Progressive Curriculum Reinforcement Learning for Advanced Multimodal Reasoning
Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in understanding common visual elements such as …
LASA Team, Weiwen Xu, Hou Pong Chan, Long Li, Mahani Aljunied, Ruifeng Yuan, Jianyu Wang, Chenghao Xiao, Guizhen Chen, Chaoqun Liu, Zhaodonghui Li, Yu Sun, Junao Shen, Chaojun Wang, Jie Tan, Deli Zhao, Tingyang Xu, Hao Zhang, Yu Rong
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Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval
The performance of Dense retrieval (DR) is significantly influenced by the quality of negative sampling. Traditional DR methods …
Xiaopeng Li, Xiangyang Li, Hao Zhang, Zhaocheng Du, Pengyue Jia, Yichao Wang, Xiangyu Zhao, Huifeng Guo, Ruiming Tang
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SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval
Hesitation and Tolerance in Recommender Systems
User interactions in recommender systems are inherently complex, often involving behaviors that go beyond simple acceptance or …
Kuan Zou, Aixin Sun, Xuemeng Jiang, Yitong Ji, Hao Zhang, Jing Wang, Ruijie Guo
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Hesitation and Tolerance in Recommender Systems
Learning to Compress Contexts for Efficient Knowledge-based Visual Question Answering
Multimodal Large Language Models (MLLMs) have demonstrated great zero-shot performance on visual question answering (VQA). However, …
Weixi Weng, Jieming Zhu, Hao Zhang, Xiaojun Meng, Rui Zhang, Chun Yuan
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Learning to Compress Contexts for Efficient Knowledge-based Visual Question Answering
All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era
Recommender systems (RS) are vital for managing information overload and delivering personalized content, responding to users’ …
Bo Chen, Xinyi Dai, Huifeng Guo, Wei Guo, Weiwen Liu, Yong Liu, Jiarui Qin, Ruiming Tang, Yichao Wang, Chuhan Wu, Yaxiong Wu, Hao Zhang
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All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era
How Can Recommender Systems Benefit from Large Language Models: A Survey
With the rapid development of online services and web applications, recommender systems (RS) have become increasingly indispensable for …
Jianghao Lin, Xinyi Dai, Yunjia Xi, Weiwen Liu, Bo Chen, Hao Zhang, Yong Liu, Chuhan Wu, Xiangyang Li, Chenxu Zhu, Huifeng Guo, Yong Yu, Ruiming Tang, Weinan Zhang
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How Can Recommender Systems Benefit from Large Language Models: A Survey
Evaluating the External and Parametric Knowledge Fusion of Large Language Models
Integrating external knowledge into large language models (LLMs) presents a promising solution to overcome the limitations imposed by …
Hao Zhang, Yuyang Zhang, Xiaoguang Li, Wenxuan Shi, Haonan Xu, Huanshuo Liu, Yasheng Wang, Lifeng Shang, Qun Liu, Yong Liu, Ruiming Tang
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Evaluating the External and Parametric Knowledge Fusion of Large Language Models