most citedTickIt: Leveraging Large Language Models for Automated Ticket Escalation

4 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025

MedGEN-Bench: A Contextually Entangled Benchmark for Open-ended Multimodal Medical Generation

Junjie Yang, Yuhao Yan, Gang Wu +12

Medical vision-language models (VLMs) are increasingly expected to support clinical workflows through diagnostic text and relevant medical images. However, current medical visual b…

cs.CV2025★ 1 cited

Seed1.5-VL Technical Report

Dong Guo, Faming Wu, Feida Zhu +194

We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…

cs.SE2025★ 4 cited

TickIt: Leveraging Large Language Models for Automated Ticket Escalation

Fengrui Liu, Xiao He, Tieying Zhang +6

In large-scale cloud service systems, support tickets serve as a critical mechanism for resolving customer issues and maintaining service quality. However, traditional manual ticke…

cs.CV2025

SKALD: Learning-Based Shot Assembly for Coherent Multi-Shot Video Creation

Chen Yi Lu, Md Mehrab Tanjim, Ishita Dasgupta +4

We present SKALD, a multi-shot video assembly method that constructs coherent video sequences from candidate shots with minimal reliance on text. Central to our approach is the Lea…

cs.CL2024

Knowledge Editing for Large Language Model with Knowledge Neuronal Ensemble

Yongchang Li, Yujin Zhu, Tao Yan +3

As real-world knowledge is constantly evolving, ensuring the timeliness and accuracy of a model's knowledge is crucial. This has made knowledge editing in large language models inc…