42 citations · 54 across the 26 of their papers we have counts for
27 papers
EchoRec: Multi-Item Prediction-Empowered Generative Recommendation via Cycle-Consistent Preference Alignment
Haokai Ma, Aoqi Hu, Yueao Xing +5
Generative recommendation autoregressively generates the semantic IDs of the target item, unifying preference modeling and index retrieval within the shared token space. Recent att…
An Extensive Benchmark for Single-round and Multi-round Instruction-based Image Editing
Yiwei Ma, Ke Ye, Weihuang Lin +4
In recent years, there have been notable advancements in the area of instruction-based image editing (IIE), which focuses on the automatic alteration of input images using a model.…
CFALR: Collaborative Filtering-Augmented Large Language Model for Personalized Fashion Outfit Recommendation
Yujuan Ding, Junrong Liao, Yunshan Ma +4
Personalized outfit recommendation poses a significant challenge in e-commerce and social media platforms, requiring systems that balance user preferences with aesthetic compatibil…
Less Data Approximates More: Earning Faithful Confidence in High-Stakes Domains
Haokai Ma, Lee Yan Zhen, Gang Yang +4
Large language models are increasingly deployed in high-stakes domains, where confident yet incorrect inferences may cause severe real-world harm, bringing the long-overlooked issu…
ThinkTank-ME: A Multi-Expert Framework for Middle East Event Forecasting
Haoxuan Li, He Chang, Yunshan Ma +4
Event forecasting is inherently influenced by multifaceted considerations, including international relations, regional historical dynamics, and cultural contexts. However, existing…
Reasoning on Time-Series for Financial Technical Analysis
Kelvin J. L. Koa, Jan Chen, Yunshan Ma +2
While Large Language Models have been used to produce interpretable stock forecasts, they mainly focus on analyzing textual reports but not historical price data, also known as Tec…
Causal-Entity Reflected Egocentric Traffic Accident Video Synthesis
Lei-lei Li, Jianwu Fang, Junbin Xiao +5
Egocentricly comprehending the causes and effects of car accidents is crucial for the safety of self-driving cars, and synthesizing causal-entity reflected accident videos can faci…
LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
Yingzhi He, Xiaohao Liu, An Zhang +2
Sequential recommendation aims to predict users' future interactions by modeling collaborative filtering (CF) signals from historical behaviors of similar users or items. Tradition…
Distilling Transitional Pattern to Large Language Models for Multimodal Session-based Recommendation
Jiajie Su, Qiyong Zhong, Yunshan Ma +5
Session-based recommendation (SBR) predicts the next item based on anonymous sessions. Traditional SBR explores user intents based on ID collaborations or auxiliary content. To fur…
Large Language Model Empowered Recommendation Meets All-domain Continual Pre-Training
Haokai Ma, Yunshan Ma, Ruobing Xie +5
Recent research efforts have investigated how to integrate Large Language Models (LLMs) into recommendation, capitalizing on their semantic comprehension and open-world knowledge f…
Extending Visual Dynamics for Video-to-Music Generation
Xiaohao Liu, Teng Tu, Yunshan Ma +1
Music profoundly enhances video production by improving quality, engagement, and emotional resonance, sparking growing interest in video-to-music generation. Despite recent advance…
Integrate Temporal Graph Learning into LLM-based Temporal Knowledge Graph Model
He Chang, Jie Wu, Zhulin Tao +3
Temporal Knowledge Graph Forecasting (TKGF) aims to predict future events based on the observed events in history. Recently, Large Language Models (LLMs) have exhibited remarkable…
Headache to Overstock? Promoting Long-tail Items through Debiased Product Bundling
Shuo Xu, Haokai Ma, Yunshan Ma +4
Product bundling aims to organize a set of thematically related items into a combined bundle for shipment facilitation and item promotion. To increase the exposure of fresh or over…
Temporal Relational Reasoning of Large Language Models for Detecting Stock Portfolio Crashes
Kelvin J. L. Koa, Yunshan Ma, Yi Xu +3
Stock portfolios are often exposed to rare consequential events (e.g., 2007 global financial crisis, 2020 COVID-19 stock market crash), as they do not have enough historical inform…
AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models
Junfeng Fang, Houcheng Jiang, Kun Wang +5
Large language models (LLMs) often exhibit hallucinations due to incorrect or outdated knowledge. Hence, model editing methods have emerged to enable targeted knowledge updates. To…
MM-Forecast: A Multimodal Approach to Temporal Event Forecasting with Large Language Models
Haoxuan Li, Zhengmao Yang, Yunshan Ma +3
We study an emerging and intriguing problem of multimodal temporal event forecasting with large language models. Compared to using text or graph modalities, the investigation of ut…
Fine-tuning Multimodal Large Language Models for Product Bundling
Xiaohao Liu, Jie Wu, Zhulin Tao +3
Recent advances in product bundling have leveraged multimodal information through sophisticated encoders, but remain constrained by limited semantic understanding and a narrow scop…
A Comprehensive Evaluation of Large Language Models on Temporal Event Forecasting
He Chang, Chenchen Ye, Zhulin Tao +5
Recently, Large Language Models (LLMs) have demonstrated great potential in various data mining tasks, such as knowledge question answering, mathematical reasoning, and commonsense…
LARP: Language Audio Relational Pre-training for Cold-Start Playlist Continuation
Rebecca Salganik, Xiaohao Liu, Yunshan Ma +2
As online music consumption increasingly shifts towards playlist-based listening, the task of playlist continuation, in which an algorithm suggests songs to extend a playlist in a…
Analyzing Temporal Complex Events with Large Language Models? A Benchmark towards Temporal, Long Context Understanding
Zhihan Zhang, Yixin Cao, Chenchen Ye +3
The digital landscape is rapidly evolving with an ever-increasing volume of online news, emphasizing the need for swift and precise analysis of complex events. We refer to the comp…
CIRP: Cross-Item Relational Pre-training for Multimodal Product Bundling
Yunshan Ma, Yingzhi He, Wenjun Zhong +3
Product bundling has been a prevailing marketing strategy that is beneficial in the online shopping scenario. Effective product bundling methods depend on high-quality item represe…
FashionReGen: LLM-Empowered Fashion Report Generation
Yujuan Ding, Yunshan Ma, Wenqi Fan +3
Fashion analysis refers to the process of examining and evaluating trends, styles, and elements within the fashion industry to understand and interpret its current state, generatin…
Contrastive Pre-training for Deep Session Data Understanding
Zixuan Li, Lizi Liao, Yunshan Ma +1
Session data has been widely used for understanding user's behavior in e-commerce. Researchers are trying to leverage session data for different tasks, such as purchase intention p…
Learning to Ask Critical Questions for Assisting Product Search
Zixuan Li, Lizi Liao, Tat-Seng Chua
Product search plays an essential role in eCommerce. It was treated as a special type of information retrieval problem. Most existing works make use of historical data to improve t…