244 citations · 1.5k across the 71 of their papers we have counts for
72 papers
TextBind: Multi-turn Interleaved Multimodal Instruction-following in the Wild
Huayang Li, Siheng Li, Deng Cai +5
Large language models with instruction-following abilities have revolutionized the field of artificial intelligence. These models show exceptional generalizability to tackle variou…
Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models
Yue Zhang, Yafu Li, Leyang Cui +13
While large language models (LLMs) have demonstrated remarkable capabilities across a range of downstream tasks, a significant concern revolves around their propensity to exhibit h…
TeCH: Text-guided Reconstruction of Lifelike Clothed Humans
Yangyi Huang, Hongwei Yi, Yuliang Xiu +4
Despite recent research advancements in reconstructing clothed humans from a single image, accurately restoring the "unseen regions" with high-level details remains an unsolved cha…
Large Language Models Meet Harry Potter: A Bilingual Dataset for Aligning Dialogue Agents with Characters
Nuo Chen, Yan Wang, Haiyun Jiang +5
In recent years, Dialogue-style Large Language Models (LLMs) such as ChatGPT and GPT4 have demonstrated immense potential in constructing open-domain dialogue agents. However, alig…
Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification
Yang Liu, Weifeng Zhang, Chao Xiang +3
Few-shot learning (FSL) aims to learn a classifier that can be easily adapted to accommodate new tasks not seen during training, given only a few examples. To handle the limited-da…
Assessing Dialogue Systems with Distribution Distances
Jiannan Xiang, Yahui Liu, Deng Cai +3
An important aspect of developing dialogue systems is how to evaluate and compare the performance of different systems. Existing automatic evaluation metrics are based on turn-leve…
Dynamic Semantic Graph Construction and Reasoning for Explainable Multi-hop Science Question Answering
Weiwen Xu, Huihui Zhang, Deng Cai +1
Knowledge retrieval and reasoning are two key stages in multi-hop question answering (QA) at web scale. Existing approaches suffer from low confidence when retrieving evidence fact…
ES-Net: Erasing Salient Parts to Learn More in Re-Identification
Dong Shen, Shuai Zhao, Jinming Hu +3
As an instance-level recognition problem, re-identification (re-ID) requires models to capture diverse features. However, with continuous training, re-ID models pay more and more a…
Non-Autoregressive Text Generation with Pre-trained Language Models
Yixuan Su, Deng Cai, Yan Wang +4
Non-autoregressive generation (NAG) has recently attracted great attention due to its fast inference speed. However, the generation quality of existing NAG models still lags behind…
Complementary Pseudo Labels For Unsupervised Domain Adaptation On Person Re-identification
Hao Feng, Minghao Chen, Jinming Hu +3
In recent years, supervised person re-identification (re-ID) models have received increasing studies. However, these models trained on the source domain always suffer dramatic perf…
LAMP: Label Augmented Multimodal Pretraining
Jia Guo, Chen Zhu, Yilun Zhao +4
Multi-modal representation learning by pretraining has become an increasing interest due to its easy-to-use and potential benefit for various Visual-and-Language~(V-L) tasks. Howev…
Narrative Incoherence Detection
Deng Cai, Yizhe Zhang, Yichen Huang +2
We propose the task of narrative incoherence detection as a new arena for inter-sentential semantic understanding: Given a multi-sentence narrative, decide whether there exist any…
EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications
Minghui Qiu, Peng Li, Chengyu Wang +8
The literature has witnessed the success of leveraging Pre-trained Language Models (PLMs) and Transfer Learning (TL) algorithms to a wide range of Natural Language Processing (NLP)…
Geometry-based Occlusion-Aware Unsupervised Stereo Matching for Autonomous Driving
Liang Peng, Dan Deng, Deng Cai
Recently, there are emerging many stereo matching methods for autonomous driving based on unsupervised learning. Most of them take advantage of reconstruction losses to remove depe…
Reducing the Teacher-Student Gap via Spherical Knowledge Disitllation
Jia Guo, Minghao Chen, Yao Hu +3
Knowledge distillation aims at obtaining a compact and effective model by learning the mapping function from a much larger one. Due to the limited capacity of the student, the stud…
Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework
Wenxiao Wang, Minghao Chen, Shuai Zhao +6
Most neural network pruning methods, such as filter-level and layer-level prunings, prune the network model along one dimension (depth, width, or resolution) solely to meet a compu…
Do Wider Neural Networks Really Help Adversarial Robustness?
Boxi Wu, Jinghui Chen, Deng Cai +2
Adversarial training is a powerful type of defense against adversarial examples. Previous empirical results suggest that adversarial training requires wider networks for better per…
Apparel-invariant Feature Learning for Apparel-changed Person Re-identification
Zhengxu Yu, Yilun Zhao, Bin Hong +5
With the rise of deep learning methods, person Re-Identification (ReID) performance has been improved tremendously in many public datasets. However, most public ReID datasets are c…
Learning to Caricature via Semantic Shape Transform
Wenqing Chu, Wei-Chih Hung, Yi-Hsuan Tsai +4
Caricature is an artistic drawing created to abstract or exaggerate facial features of a person. Rendering visually pleasing caricatures is a difficult task that requires professio…
RESA: Recurrent Feature-Shift Aggregator for Lane Detection
Tu Zheng, Hao Fang, Yi Zhang +4
Lane detection is one of the most important tasks in self-driving. Due to various complex scenarios (e.g., severe occlusion, ambiguous lanes, etc.) and the sparse supervisory signa…
Interpretable Real-Time Win Prediction for Honor of Kings, a Popular Mobile MOBA Esport
Zelong Yang, Zhufeng Pan, Yan Wang +4
With the rapid prevalence and explosive development of MOBA esports (Multiplayer Online Battle Arena electronic sports), much research effort has been devoted to automatically pred…
Adversarial Mutual Information for Text Generation
Boyuan Pan, Yazheng Yang, Kaizhao Liang +5
Recent advances in maximizing mutual information (MI) between the source and target have demonstrated its effectiveness in text generation. However, previous works paid little atte…
Stylistic Dialogue Generation via Information-Guided Reinforcement Learning Strategy
Yixuan Su, Deng Cai, Yan Wang +4
Stylistic response generation is crucial for building an engaging dialogue system for industrial use. While it has attracted much research interest, existing methods often generate…
The World is Not Binary: Learning to Rank with Grayscale Data for Dialogue Response Selection
Zibo Lin, Deng Cai, Yan Wang +3
Response selection plays a vital role in building retrieval-based conversation systems. Despite that response selection is naturally a learning-to-rank problem, most prior works ta…