64 citations · 66 across the 9 of their papers we have counts for
9 papers
MGRetrieval: Memory-Guided Reflective Retrieval for Long-Term Dialogue Agents
Tan Wang, Yunwei Dong
Large Language Models (LLMs) have made significant progress in dialogue, yet redundant memory contexts severely limit their effectiveness in long-term dialogue agents. External mem…
OmniWeaving: Towards Unified Video Generation with Free-form Composition and Reasoning
Kaihang Pan, Qi Tian, Jianwei Zhang +12
While proprietary systems such as Seedance-2.0 have achieved remarkable success in omni-capable video generation, the academic research community lags far behind: most of its model…
Grounded Token Initialization for New Vocabulary in LMs for Generative Recommendation
Daiwei Chen, Zhoutong Fu, Chengming Jiang +12
Language models (LMs) are increasingly extended with new learnable vocabulary tokens for domain-specific tasks, such as Semantic-ID tokens in generative recommendation. The standar…
LANTERN: Scalable Distillation of Large Language Models for Job-Person Fit and Explanation
Zhoutong Fu, Yihan Cao, Yi-Lin Chen +16
Large language models (LLMs) have achieved strong performance across a wide range of natural language processing tasks. However, deploying LLMs at scale for domain specific applica…
Large Language Model Unlearning for Source Code
Xue Jiang, Yihong Dong, Huangzhao Zhang +9
While Large Language Models (LLMs) excel at code generation, their inherent tendency toward verbatim memorization of training data introduces critical risks like copyright infringe…
TIGeR: Unifying Text-to-Image Generation and Retrieval with Large Multimodal Models
Leigang Qu, Haochuan Li, Tan Wang +4
How humans can effectively and efficiently acquire images has always been a perennial question. A classic solution is text-to-image retrieval from an existing database; however, th…
Relevant or Random: Can LLMs Truly Perform Analogical Reasoning?
Chengwei Qin, Wenhan Xia, Tan Wang +5
Analogical reasoning is a unique ability of humans to address unfamiliar challenges by transferring strategies from relevant past experiences. One key finding in psychology is that…
Enhance Image Classification via Inter-Class Image Mixup with Diffusion Model
Zhicai Wang, Longhui Wei, Tan Wang +5
Text-to-image (T2I) generative models have recently emerged as a powerful tool, enabling the creation of photo-realistic images and giving rise to a multitude of applications. Howe…
DeVLBert: Learning Deconfounded Visio-Linguistic Representations
Shengyu Zhang, Tan Jiang, Tan Wang +6
In this paper, we propose to investigate the problem of out-of-domain visio-linguistic pretraining, where the pretraining data distribution differs from that of downstream data on…