3.2k citations · 3.9k across the 76 of their papers we have counts for
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Learn More, Forget Less: A Gradient-Aware Data Selection Approach for LLM
Yibai Liu, Shihang Wang, Zeming Liu +5
Despite large language models (LLMs) have achieved impressive achievements across numerous tasks, supervised fine-tuning (SFT) remains essential for adapting these models to specia…
GODBench: A Benchmark for Multimodal Large Language Models in Video Comment Art
Yiming Lei, Chenkai Zhang, Zeming Liu +5
Video Comment Art enhances user engagement by providing creative content that conveys humor, satire, or emotional resonance, requiring a nuanced and comprehensive grasp of cultural…
ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations
Yiming Lei, Zhizheng Yang, Zeming Liu +5
Multi-modal large language models have demonstrated remarkable zero-shot abilities and powerful image-understanding capabilities. However, the existing open-source multi-modal mode…
KwaiChat: A Large-Scale Video-Driven Multilingual Mixed-Type Dialogue Corpus
Xiaoming Shi, Zeming Liu, Yiming Lei +8
Video-based dialogue systems, such as education assistants, have compelling application value, thereby garnering growing interest. However, the current video-based dialogue systems…
A Survey on Data Synthesis and Augmentation for Large Language Models
Ke Wang, Jiahui Zhu, Minjie Ren +8
The success of Large Language Models (LLMs) is inherently linked to the availability of vast, diverse, and high-quality data for training and evaluation. However, the growth rate o…
Visual and Textual Sentiment Analysis Using Deep Fusion Convolutional Neural Networks
Xingyue Chen, Yunhong Wang, Qingjie Liu
Sentiment analysis is attracting more and more attentions and has become a very hot research topic due to its potential applications in personalized recommendation, opinion mining,…