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Reverse Modeling in Large Language Models
Humans are accustomed to reading and writing in a forward manner, and this natural bias extends to text understanding in …
Sicheng Yu, Yuanchen Xu, Cunxiao Du, Yanying Zhou, Minghui Qiu, Qianru Sun, Hao Zhang, Jiawei Wu
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Reverse Modeling in Large Language Models
Frame-Voyager: Learning to Query Frames for Video Large Language Models
Video Large Language Models (Video-LLMs) have made remarkable progress in video understanding tasks. However, they are constrained by …
Sicheng Yu, Chengkai Jin, Huanyu Wang, Zhenghao Chen, Sheng Jin, Zhongrong Zuo, Xioalei Xu, Zhenbang Sun, Bingni Zhang, Jiawei Wu, Hao Zhang, Qianru Sun
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Frame-Voyager: Learning to Query Frames for Video Large Language Models
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
CoIR: A Comprehensive Benchmark for Code Information Retrieval Models
Despite the substantial success of Information Retrieval (IR) in various NLP tasks, most IR systems predominantly handle queries and …
Xiangyang Li, Kuicai Dong, Yi Quan Lee, Wei Xia, Yichun Yin, Hao Zhang, Yong Liu, Yasheng Wang, Ruiming Tang
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CoIR: A Comprehensive Benchmark for Code Information Retrieval Models
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
CtrlA: Adaptive Retrieval-Augmented Generation via Inherent Control
Retrieval-augmented generation (RAG) has emerged as a promising solution for mitigating hallucinations of large language models (LLMs) …
Huanshuo Liu, Hao Zhang, Zhijiang Guo, Kuicai Dong, Xiangyang Li, Yi Quan Lee, Cong Zhang, Yong Liu
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CtrlA: Adaptive Retrieval-Augmented Generation via Inherent Control
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
Meta-Task Planning for Language Agents
The rapid advancement of neural language models has sparked a new surge of intelligent agent research. Unlike traditional agents, large …
Cong Zhang, Derrick Goh Xin Deik, Dexun Li, Hao Zhang, Yong Liu
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Meta-Task Planning for Language Agents
Towards Debiasing Temporal Sentence Grounding in Video
The temporal sentence grounding in video (TSGV) task is to locate a temporal moment from an untrimmed video, to match a language query, …
Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou
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Towards Debiasing Temporal Sentence Grounding in Video