8 papers
EARS: Explanatory Abstention for Reliable Sub-Agent Modeling in Large-scale Multi-Agent Systems
Shuang Xie, Yunan Lu, Han Li +1
In large-scale enterprise settings, centralized multi-agent systems (MAS) are increasingly adopted, in which a coordinator delegates user requests to lightweight, domain-specialize…
SimGym: A Framework for A/B Test Simulation in E-Commerce with Traffic-Grounded VLM Agents
Han Li, Vibhor Malik, Zahra Zanjani Foumani +17
A/B testing remains the gold standard for evaluating modifications to e-commerce storefronts, yet it diverts traffic, requires weeks to reach statistical significance, and risks de…
ShopGym: An Integrated Framework for Realistic Simulation and Scalable Benchmarking of E-Commerce Web Agents
Chinmay Savadikar, Mingyu Zhao, Yuanzheng Zhu +5
Developing and evaluating e-commerce web agents requires environments that preserve meaningful task structure while enabling controllable, reproducible, and scalable scientific com…
SimPersona: Learning Discrete Buyer Personas from Raw Clickstreams for Grounded E-Commerce Agents
Zahra Zanjani Foumani, Alberto Castelo, Shuang Xie +3
LLM-based web agents can navigate live storefronts, yet they often collapse to a single "average buyer" policy, failing to capture the heterogeneous and distributional nature of re…
Resource-Friendly Dynamic Enhancement Chain for Multi-Hop Question Answering
Binquan Ji, Haibo Luo, Yifei Lu +6
Knowledge-intensive multi-hop question answering (QA) tasks, which require integrating evidence from multiple sources to address complex queries, often necessitate multiple rounds…
M-LLM Based Video Frame Selection for Efficient Video Understanding
Kai Hu, Feng Gao, Xiaohan Nie +8
Recent advances in Multi-Modal Large Language Models (M-LLMs) show promising results in video reasoning. Popular Multi-Modal Large Language Model (M-LLM) frameworks usually apply n…
Multimodal Instruction Tuning with Hybrid State Space Models
Jianing Zhou, Han Li, Shuai Zhang +5
Handling lengthy context is crucial for enhancing the recognition and understanding capabilities of multimodal large language models (MLLMs) in applications such as processing high…
Label-Guided Prompt for Multi-label Few-shot Aspect Category Detection
ChaoFeng Guan, YaoHui Zhu, Yu Bai +1
Multi-label few-shot aspect category detection aims at identifying multiple aspect categories from sentences with a limited number of training instances. The representation of sent…