579 citations · 3k across the 98 of their papers we have counts for
98 papers
Dynamic Multimodal Fusion via Meta-Learning Towards Micro-Video Recommendation
Han Liu, Yinwei Wei, Fan Liu +3
Multimodal information (e.g., visual, acoustic, and textual) has been widely used to enhance representation learning for micro-video recommendation. For integrating multimodal info…
Causal Distillation for Alleviating Performance Heterogeneity in Recommender Systems
Shengyu Zhang, Ziqi Jiang, Jiangchao Yao +7
Recommendation performance usually exhibits a long-tail distribution over users -- a small portion of head users enjoy much more accurate recommendation services than the others. W…
TAT-LLM: A Specialized Language Model for Discrete Reasoning over Tabular and Textual Data
Fengbin Zhu, Ziyang Liu, Fuli Feng +3
In this work, we address question answering (QA) over a hybrid of tabular and textual data that are very common content on the Web (e.g. SEC filings), where discrete reasoning capa…
Temporally and Distributionally Robust Optimization for Cold-Start Recommendation
Xinyu Lin, Wenjie Wang, Jujia Zhao +3
Collaborative Filtering (CF) recommender models highly depend on user-item interactions to learn CF representations, thus falling short of recommending cold-start items. To address…
Robust Collaborative Filtering to Popularity Distribution Shift
An Zhang, Wenchang Ma, Jingnan Zheng +2
In leading collaborative filtering (CF) models, representations of users and items are prone to learn popularity bias in the training data as shortcuts. The popularity shortcut tri…
Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation
Xinyu Lin, Wenjie Wang, Yongqi Li +3
Harnessing Large Language Models (LLMs) for recommendation is rapidly emerging, which relies on two fundamental steps to bridge the recommendation item space and the language space…
Context-aware Event Forecasting via Graph Disentanglement
Yunshan Ma, Chenchen Ye, Zijian Wu +3
Event forecasting has been a demanding and challenging task throughout the entire human history. It plays a pivotal role in crisis alarming and disaster prevention in various aspec…
LayoutLLM-T2I: Eliciting Layout Guidance from LLM for Text-to-Image Generation
Leigang Qu, Shengqiong Wu, Hao Fei +2
In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current mode…
Constructing Holistic Spatio-Temporal Scene Graph for Video Semantic Role Labeling
Yu Zhao, Hao Fei, Yixin Cao +5
Video Semantic Role Labeling (VidSRL) aims to detect the salient events from given videos, by recognizing the predict-argument event structures and the interrelationships between e…
Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition
Bobo Li, Hao Fei, Lizi Liao +5
It has been a hot research topic to enable machines to understand human emotions in multimodal contexts under dialogue scenarios, which is tasked with multimodal emotion analysis i…
Redundancy-aware Transformer for Video Question Answering
Yicong Li, Xun Yang, An Zhang +3
This paper identifies two kinds of redundancy in the current VideoQA paradigm. Specifically, the current video encoders tend to holistically embed all video clues at different gran…
SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning
Keyu Duan, Qian Liu, Tat-Seng Chua +4
Textual graphs (TGs) are graphs whose nodes correspond to text (sentences or documents), which are widely prevalent. The representation learning of TGs involves two stages: (i) uns…
Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructions
Juncheng Li, Kaihang Pan, Zhiqi Ge +7
Recent advancements in Multimodal Large Language Models (MLLMs) have been utilizing Visual Prompt Generators (VPGs) to convert visual features into tokens that LLMs can recognize.…
XNLP: An Interactive Demonstration System for Universal Structured NLP
Hao Fei, Meishan Zhang, Min Zhang +1
Structured Natural Language Processing (XNLP) is an important subset of NLP that entails understanding the underlying semantic or syntactic structure of texts, which serves as a fo…
Discovering Spatio-Temporal Rationales for Video Question Answering
Yicong Li, Junbin Xiao, Chun Feng +2
This paper strives to solve complex video question answering (VideoQA) which features long video containing multiple objects and events at different time. To tackle the challenge,…
Revisiting Conversation Discourse for Dialogue Disentanglement
Bobo Li, Hao Fei, Fei Li +5
Dialogue disentanglement aims to detach the chronologically ordered utterances into several independent sessions. Conversation utterances are essentially organized and described by…
Reasoning Implicit Sentiment with Chain-of-Thought Prompting
Hao Fei, Bobo Li, Qian Liu +3
While sentiment analysis systems try to determine the sentiment polarities of given targets based on the key opinion expressions in input texts, in implicit sentiment analysis (ISA…
Constructing Code-mixed Universal Dependency Forest for Unbiased Cross-lingual Relation Extraction
Hao Fei, Meishan Zhang, Min Zhang +1
Latest efforts on cross-lingual relation extraction (XRE) aggressively leverage the language-consistent structural features from the universal dependency (UD) resource, while they…
Computational Technologies for Fashion Recommendation: A Survey
Yujuan Ding, Zhihui Lai, P. Y. Mok +1
Fashion recommendation is a key research field in computational fashion research and has attracted considerable interest in the computer vision, multimedia, and information retriev…
Discovering Dynamic Causal Space for DAG Structure Learning
Fangfu Liu, Wenchang Ma, An Zhang +3
Discovering causal structure from purely observational data (i.e., causal discovery), aiming to identify causal relationships among variables, is a fundamental task in machine lear…
Cross2StrA: Unpaired Cross-lingual Image Captioning with Cross-lingual Cross-modal Structure-pivoted Alignment
Shengqiong Wu, Hao Fei, Wei Ji +1
Unpaired cross-lingual image captioning has long suffered from irrelevancy and disfluency issues, due to the inconsistencies of the semantic scene and syntax attributes during tran…
Scene Graph as Pivoting: Inference-time Image-free Unsupervised Multimodal Machine Translation with Visual Scene Hallucination
Hao Fei, Qian Liu, Meishan Zhang +2
In this work, we investigate a more realistic unsupervised multimodal machine translation (UMMT) setup, inference-time image-free UMMT, where the model is trained with source-text…
Generating Visual Spatial Description via Holistic 3D Scene Understanding
Yu Zhao, Hao Fei, Wei Ji +4
Visual spatial description (VSD) aims to generate texts that describe the spatial relations of the given objects within images. Existing VSD work merely models the 2D geometrical v…
Dual Semantic Knowledge Composed Multimodal Dialog Systems
Xiaolin Chen, Xuemeng Song, Yinwei Wei +2
Textual response generation is an essential task for multimodal task-oriented dialog systems.Although existing studies have achieved fruitful progress, they still suffer from two c…