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The advent of Large Language Models (LLMs) has revolutionized various domains of artificial intelligence, including the realm of software engineering. In this research, we evaluate the efficacy of pre-trained LLMs in replicating the tasks…

软件工程 · 计算机科学 2024-06-10 Tajmilur Rahman , Rahul Singh , Mir Yousuf Sultan

Fake news detection plays a crucial role in protecting social media users and maintaining a healthy news ecosystem. Among existing works, comment-based fake news detection methods are empirically shown as promising because comments could…

计算与语言 · 计算机科学 2024-09-23 Qiong Nan , Qiang Sheng , Juan Cao , Beizhe Hu , Danding Wang , Jintao Li

This paper proposes a generative method to dynamically simulate users' short video watching journey for watch time prediction in short video recommendation. Unlike existing methods that rely on multimodal features for video content…

信息检索 · 计算机科学 2025-09-23 Chao Feng , Yanze Zhang , Chenghao Zhang

Automatically generating concise, informative comments for source code can lighten documentation effort and accelerate program comprehension. Retrieval-augmented approaches first fetch code snippets with existing comments and then…

软件工程 · 计算机科学 2025-07-25 Tien P. T. Le , Anh M. T. Bui , Huy N. D. Pham , Alessio Bucaioni , Phuong T. Nguyen

Generating humorous memes is a challenging multimodal task that moves beyond direct image-to-caption supervision. It requires a nuanced reasoning over visual content, contextual cues, and subjective humor. To bridge this gap between visual…

机器学习 · 计算机科学 2026-01-21 Xueyan Li , Yingyi Xue , Mengjie Jiang , Qingzi Zhu , Yazhe Niu

Can out-of-the-box pretrained Large Language Models (LLMs) detect human affect successfully when observing a video? To address this question, for the first time, we evaluate comprehensively the capacity of popular LLMs for successfully…

计算机视觉与模式识别 · 计算机科学 2026-01-30 David Melhart , Matthew Barthet , Georgios N. Yannakakis

This paper addresses the critical and underexplored challenge of long video understanding with low computational budgets. We propose LongVideo-R1, an active, reasoning-equipped multimodal large language model (MLLM) agent designed for…

计算机视觉与模式识别 · 计算机科学 2026-04-16 Jihao Qiu , Lingxi Xie , Xinyue Huo , Qi Tian , Qixiang Ye

Multimodal large language models (MLLMs) are flourishing, but mainly focus on images with less attention than videos, especially in sub-fields such as prompt engineering, video chain-of-thought (CoT), and instruction tuning on videos.…

计算机视觉与模式识别 · 计算机科学 2024-07-09 Yan Wang , Yawen Zeng , Jingsheng Zheng , Xiaofen Xing , Jin Xu , Xiangmin Xu

Long texts are ubiquitous on social platforms, yet readers often face information overload and struggle to locate key content. Comments provide valuable external perspectives for understanding, questioning, and complementing the text, but…

人机交互 · 计算机科学 2026-04-03 Shuai Chen , Lei Han , Haoran Zhang , Kaihao Liu , Zhaoman Zhong

Recent multimodal large language models (MLLMs) have shown strong capabilities in general video understanding, driving growing interest in automatic sports commentary generation. However, existing benchmarks for this task focus exclusively…

计算机视觉与模式识别 · 计算机科学 2026-04-07 Kaiwen Wang , Kaili Zheng , Rongrong Deng , Yiming Shi , Chenyi Guo , Ji Wu

Due to the textual and repetitive nature of many Requirements Engineering (RE) artefacts, Large Language Models (LLMs) have proven useful to automate their generation and processing. In this paper, we discuss a possible approach for…

Efficient fine-tuning is vital for adapting large language models (LLMs) to downstream tasks. However, it requires non-trivial efforts to implement these methods on different models. We present LlamaFactory, a unified framework that…

计算与语言 · 计算机科学 2024-07-01 Yaowei Zheng , Richong Zhang , Junhao Zhang , Yanhan Ye , Zheyan Luo , Zhangchi Feng , Yongqiang Ma

The digital age has expanded social media and online forums, allowing free expression for nearly 45% of the global population. Yet, it has also fueled online harassment, bullying, and harmful behaviors like hate speech and toxic comments…

计算与语言 · 计算机科学 2026-03-12 Vuong M. Ngo , Cach N. Dang , Kien V. Nguyen , Mark Roantree

Creators struggle to edit long-form, narrative-rich videos not because of UI complexity, but due to the cognitive demands of searching, storyboarding, and sequencing hours of footage. Existing transcript- or embedding-based methods fall…

人工智能 · 计算机科学 2025-09-30 Zihan Ding , Xinyi Wang , Junlong Chen , Per Ola Kristensson , Junxiao Shen

Long videos contain a vast amount of information, making video-text retrieval an essential and challenging task in multimodal learning. However, existing benchmarks suffer from limited video duration, low-quality captions, and coarse…

计算机视觉与模式识别 · 计算机科学 2026-02-05 Qifeng Cai , Hao Liang , Zhaoyang Han , Hejun Dong , Meiyi Qiang , Ruichuan An , Quanqing Xu , Bin Cui , Wentao Zhang

We present PushGen, an automated framework for generating high-quality push notifications comparable to human-crafted content. With the rise of generative models, there is growing interest in leveraging LLMs for push content generation.…

Current research has explored how Generative AI can support the brainstorming process for content creators, but a gap remains in exploring support-tools for the pre-writing process. Specifically, our research is focused on supporting users…

人机交互 · 计算机科学 2024-06-19 Grace Li , Tao Long , Lydia B. Chilton

Enhancing reader engagement while preserving informational fidelity is a central challenge in controllable text generation for news media. Optimizing news headlines for reader engagement is often conflated with clickbait, resulting in…

计算与语言 · 计算机科学 2026-03-27 Yehudit Aperstein , Linoy Halifa , Sagiv Bar , Alexander Apartsin

With the growing demand for short videos and personalized content, automated Video Log (Vlog) generation has become a key direction in multimodal content creation. Existing methods mostly rely on predefined scripts, lacking dynamism and…

计算机视觉与模式识别 · 计算机科学 2025-09-03 Xiaolu Hou , Bing Ma , Jiaxiang Cheng , Xuhua Ren , Kai Yu , Wenyue Li , Tianxiang Zheng , Qinglin Lu

Reward modeling is crucial for aligning large language models (LLMs) with human preferences, especially in reinforcement learning from human feedback (RLHF). However, current reward models mainly produce scalar scores and struggle to…