34 citations · 38 across the 11 of their papers we have counts for
12 papers
CreaMem: A Scene-Aware Memory Architecture for Personalized Agents
Qixuan Sun, Yue Que, Bowei He +4
Long-term memory is a core capability for personalized LLM agents. To support it, existing memory systems organize information using various criteria such as topic segments or summ…
Learning Quantised Structure-Preserving Motion Representations for Dance Fingerprinting
Arina Kharlamova, Bowei He, Chen Ma +1
We present DANCEMATCH, an end-to-end framework for motion-based dance retrieval, the task of identifying semantically similar choreographies directly from raw video, defined as DAN…
Reasoning in Action: MCTS-Driven Knowledge Retrieval for Large Language Models
Shuqi Liu, Bowei He, Chen Ma +1
Large language models (LLMs) typically enhance their performance through either the retrieval of semantically similar information or the improvement of their reasoning capabilities…
SDrug: Bridging Protein Sequence and 3D Structure in Contrastive Representation Learning for Virtual Screening
Bowei He, Bowen Gao, Yankai Chen +5
Virtual screening (VS) is an essential task in drug discovery, focusing on the identification of small-molecule ligands that bind to specific protein pockets. Existing deep learnin…
Spatial CAPTCHA: Generatively Benchmarking Spatial Reasoning for Human-Machine Differentiation
Arina Kharlamova, Bowei He, Chen Ma +1
Online services rely on CAPTCHAs as a first line of defense against automated abuse, yet recent advances in multi-modal large language models (MLLMs) have eroded the effectiveness…
Semantic Retrieval Augmented Contrastive Learning for Sequential Recommendation
Ziqiang Cui, Yunpeng Weng, Xing Tang +8
Contrastive learning has shown effectiveness in improving sequential recommendation models. However, existing methods still face challenges in generating high-quality contrastive p…
Interpretable Triplet Importance for Personalized Ranking
Bowei He, Chen Ma
Personalized item ranking has been a crucial component contributing to the performance of recommender systems. As a representative approach, pairwise ranking directly optimizes the…
Mitigating Large Language Model Hallucination with Faithful Finetuning
Minda Hu, Bowei He, Yufei Wang +3
Large language models (LLMs) have demonstrated remarkable performance on various natural language processing tasks. However, they are prone to generating fluent yet untruthful resp…
Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing
Bowei He, Yunpeng Weng, Xing Tang +5
Uplift modeling has been widely employed in online marketing by predicting the response difference between the treatment and control groups, so as to identify the sensitive individ…
Diffusion-based Contrastive Learning for Sequential Recommendation
Ziqiang Cui, Haolun Wu, Bowei He +2
Contrastive learning has been effectively utilized to enhance the training of sequential recommendation models by leveraging informative self-supervised signals. Most existing appr…
Offline Imitation Learning with Variational Counterfactual Reasoning
Bowei He, Zexu Sun, Jinxin Liu +3
In offline imitation learning (IL), an agent aims to learn an optimal expert behavior policy without additional online environment interactions. However, in many real-world scenari…
Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization
Zexu Sun, Bowei He, Ming Ma +4
Uplift modeling has shown very promising results in online marketing. However, most existing works are prone to the robustness challenge in some practical applications. In this pap…