# HOTVCOM: Generating Buzzworthy Comments for Videos

arXiv: https://arxiv.org/abs/2409.15196 · HTML: https://mlsanity.com/paper/2409.15196/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 61 references that are in the map.
- First posted on arXiv 23 Sep 2024.

## Builds on (most cited first, 24 of 24)

- [BLEURT: Learning Robust Metrics for Text Generation](https://mlsanity.com/paper/2004.04696/) (2020)
- [GLM: General Language Model Pretraining with Autoregressive Blank Infilling](https://mlsanity.com/paper/2103.10360/) (2021)
- [Baichuan 2: Open Large-scale Language Models](https://mlsanity.com/paper/2309.10305/) (2023)
- [GIT: A Generative Image-to-text Transformer for Vision and Language](https://mlsanity.com/paper/2205.14100/) (2022)
- [Large Language Models Can Learn Temporal Reasoning](https://mlsanity.com/paper/2401.06853/) (2024)
- [Object Relational Graph with Teacher-Recommended Learning for Video Captioning](https://mlsanity.com/paper/2002.11566/) (2020)
- [CLIP4Caption: CLIP for Video Caption](https://mlsanity.com/paper/2110.06615/) (2021)
- [Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases](https://mlsanity.com/paper/2303.14742/) (2023)
- [Controllable Video Captioning with POS Sequence Guidance Based on Gated Fusion Network](https://mlsanity.com/paper/1908.10072/) (2019)
- [Describing like humans: on diversity in image captioning](https://mlsanity.com/paper/1903.12020/) (2019)
- [Object-aware Aggregation with Bidirectional Temporal Graph for Video Captioning](https://mlsanity.com/paper/1906.04375/) (2019)
- [GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation](https://mlsanity.com/paper/2303.14655/) (2023)
- [MAPO: Boosting Large Language Model Performance with Model-Adaptive Prompt Optimization](https://mlsanity.com/paper/2407.04118/) (2024)
- [O2NA: An Object-Oriented Non-Autoregressive Approach for Controllable Video Captioning](https://mlsanity.com/paper/2108.02359/) (2021)
- [Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation](https://mlsanity.com/paper/2201.05088/) (2022)
- [GL-RG: Global-Local Representation Granularity for Video Captioning](https://mlsanity.com/paper/2205.10706/) (2022)
- [NEVLP: Noise-Robust Framework for Efficient Vision-Language Pre-training](https://mlsanity.com/paper/2409.09582/) (2024)
- [LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts](https://mlsanity.com/paper/1809.04938/) (2018)
- [XMeCap: Meme Caption Generation with Sub-Image Adaptability](https://mlsanity.com/paper/2407.17152/) (2024)
- [Can Pre-trained Language Models Understand Chinese Humor?](https://mlsanity.com/paper/2407.04105/) (2024)
- [A survey on fairness of large language models in e-commerce: progress, application, and challenge](https://mlsanity.com/paper/2405.13025/) (2024)
- [COSMic: A Coherence-Aware Generation Metric for Image Descriptions](https://mlsanity.com/paper/2109.05281/) (2021)
- [ViCo: Engaging Video Comment Generation with Human Preference Rewards](https://mlsanity.com/paper/2308.11171/) (2023)
- [Knowledge Enhanced Model for Live Video Comment Generation](https://mlsanity.com/paper/2304.14657/) (2023)

## Built on by (most cited first, 7 of 7)

- [GODBench: A Benchmark for Multimodal Large Language Models in Video Comment Art](https://mlsanity.com/paper/2505.11436/) (2025)
- [Domain Specific Benchmarks for Evaluating Multimodal Large Language Models](https://mlsanity.com/paper/2506.12958/) (2025)
- [HotComment: A Benchmark for Evaluating Popularity of Online Comments](https://mlsanity.com/paper/2604.25614/) (2026)
- [Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models](https://mlsanity.com/paper/2410.19241/) (2024)
- [Pre-trained Graphformer-based Ranking at Web-scale Search (Extended Abstract)](https://mlsanity.com/paper/2409.16590/) (2024)
- [Generative Pre-trained Ranking Model with Over-parameterization at Web-Scale (Extended Abstract)](https://mlsanity.com/paper/2409.16594/) (2024)
- [Ottilie: A Socially Intelligent Virtual Host for Sales-Driven Live Commerce](https://mlsanity.com/paper/2605.14542/) (2026)

## Abstract (arXiv)

In the era of social media video platforms, popular ``hot-comments'' play a crucial role in attracting user impressions of short-form videos, making them vital for marketing and branding purpose. However, existing research predominantly focuses on generating descriptive comments or ``danmaku'' in English, offering immediate reactions to specific video moments. Addressing this gap, our study introduces textscHotVCom, the largest Chinese video hot-comment dataset, comprising 94k diverse videos and 137 million comments. We also present the textttComHeat framework, which synergistically integrates visual, auditory, and textual data to generate influential hot-comments on the Chinese video dataset. Empirical evaluations highlight the effectiveness of our framework, demonstrating its excellence on both the newly constructed and existing datasets.