Publications (8)
SynerGen: Contextualized Generative Recommender for Unified Search and Recommendation
Vianne R. Gao, Chen Xue, Marc Versage +11
The dominant retrieve-then-rank pipeline in large-scale recommender systems suffers from mis-calibration and engineering overhead due to its architectural split and differing optim…
Exploring Reasoning-Infused Text Embedding with Large Language Models for Zero-Shot Dense Retrieval
Yuxiang Liu, Tian Wang, Gourab Kundu +6
Transformer-based models such as BERT and E5 have significantly advanced text embedding by capturing rich contextual representations. However, many complex real-world queries requi…
Shop-R1: Rewarding LLMs to Simulate Human Behavior in Online Shopping via Reinforcement Learning
Yimeng Zhang, Tian Wang, Jiri Gesi +14
Large Language Models (LLMs) have recently demonstrated strong potential in generating 'believable human-like' behavior in web environments. Prior work has explored augmenting trai…
GraphStorm: all-in-one graph machine learning framework for industry applications
Da Zheng, Xiang Song, Qi Zhu +13
Graph machine learning (GML) is effective in many business applications. However, making GML easy to use and applicable to industry applications with massive datasets remain challe…
GRIL: Knowledge Graph Retrieval-Integrated Learning with Large Language Models
Jialin Chen, Houyu Zhang, Seongjun Yun +6
Retrieval-Augmented Generation (RAG) has significantly mitigated the hallucinations of Large Language Models (LLMs) by grounding the generation with external knowledge. Recent exte…
See, Think, Act: Online Shopper Behavior Simulation with VLM Agents
Yimeng Zhang, Jiri Gesi, Ran Xue +10
LLMs have recently demonstrated strong potential in simulating online shopper behavior. Prior work has improved action prediction by applying SFT on action traces with LLM-generate…
3D Primitives are a Spatial Language for VLMs
Junze Liu, Kun Qian, Florian Dubost +8
Vision-language models (VLMs) exhibit a striking paradox: they can generate executable code that reconstructs a 3D scene from geometric primitives with correct object counts, class…
InfoPO: On Mutual Information Maximization for Large Language Model Alignment
Teng Xiao, Zhen Ge, Sujay Sanghavi +5
We study the post-training of large language models (LLMs) with human preference data. Recently, direct preference optimization and its variants have shown considerable promise in…