activity
20232026
most citedImproving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty

2 citations · 5 across the 7 of their papers we have counts for

collaborators

9 papers

cs.AI2026

Pay for the Fault, Not the Flow: Label-Free In-Flow Multi-Agent Workflow Optimization

Xuehang Guo, Haoyu Wang, Shengyu Chen +4

Large language models (LLMs) increasingly construct multi-agent workflows that decompose a complex task and assign specialist agents from a pool. However, building such a workflow…

cs.LG2026

Quantifying Event Impacts on Time Series via Multiscale Contrastive Learning

Yiming Sun, Shengyu Chen, Zhengzhang Chen +3

Shocks that spread through the web, such as cybersecurity breach disclosures, can abruptly disrupt financial time series and cause substantial abnormal losses. While these events a…

cs.IR2026

HARP: Hierarchical Adaptive Ranking with Preference-Adaptive Fusion for Query-Based CVE Prioritization

Haochen Liu, Zhengzhang Chen, Haoyu Wang +3

Vulnerability prioritization is inherently preference dependent, since the same CVE can receive different remediation priority under different operational preference scenarios. Exi…

cs.LG2026

The Power of Order: Fooling LLMs with Adversarial Table Permutations

Xinshuai Dong, Haifeng Chen, Xuyuan Liu +5

Large Language Models have achieved remarkable success and are increasingly deployed in critical applications involving tabular data, such as Table Question Answering. However, the…

cs.AI2025

Representation Interventions Enable Lifelong Knowledge Memory Control in LLMs

Xuyuan Liu, Shengyu Chen, Xinshuai Dong +6

Large language models (LLMs) often produce incorrect or outdated content after being employed. Efficient and accurate knowledge updates without costly retraining are a major challe…

cs.CL2025★ 1 cited

Learning to Route: A Rule-Driven Agent Framework for Hybrid-Source Retrieval-Augmented Generation

Haoyue Bai, Haoyu Wang, Shengyu Chen +5

Large Language Models (LLMs) have shown remarkable performance on general Question Answering (QA), yet they often struggle in domain-specific scenarios where accurate and up-to-dat…

cs.LG2024★ 1 cited

PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization

Yuyang Ye, Lu-An Tang, Haoyu Wang +5

Achieving carbon neutrality within industrial operations has become increasingly imperative for sustainable development. It is both a significant challenge and a key opportunity fo…

cs.LG2023★ 1 cited

GLAD: Content-aware Dynamic Graphs For Log Anomaly Detection

Yufei Li, Yanchi Liu, Haoyu Wang +6

Logs play a crucial role in system monitoring and debugging by recording valuable system information, including events and states. Although various methods have been proposed to de…

cs.CL2023★ 2 cited

Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty

Chen Ling, Xujiang Zhao, Xuchao Zhang +8

Open Information Extraction (OIE) task aims at extracting structured facts from unstructured text, typically in the form of (subject, relation, object) triples. Despite the potenti…