activity
20232025
most citedSEvenLLM: Benchmarking, Eliciting, and Enhancing Abilities of Large Language Models in Cyber Threat Intelligence

5 citations · 10 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CL2025

P2P: Automated Paper-to-Poster Generation and Fine-Grained Benchmark

Tao Sun, Enhao Pan, Zhengkai Yang +8

Academic posters are vital for scholarly communication, yet their manual creation is time-consuming. However, automated academic poster generation faces significant challenges in p…

cs.CL2025

SimpleVQA: Multimodal Factuality Evaluation for Multimodal Large Language Models

Xianfu Cheng, Wei Zhang, Shiwei Zhang +16

The increasing application of multi-modal large language models (MLLMs) across various sectors have spotlighted the essence of their output reliability and accuracy, particularly t…

cs.CL2024

TableBench: A Comprehensive and Complex Benchmark for Table Question Answering

Xianjie Wu, Jian Yang, Linzheng Chai +10

Recent advancements in Large Language Models (LLMs) have markedly enhanced the interpretation and processing of tabular data, introducing previously unimaginable capabilities. Desp…

cs.CL2024★ 1 cited

Raw Text is All you Need: Knowledge-intensive Multi-turn Instruction Tuning for Large Language Model

Xia Hou, Qifeng Li, Jian Yang +8

Instruction tuning as an effective technique aligns the outputs of large language models (LLMs) with human preference. But how to generate the seasonal multi-turn dialogues from ra…

cs.PL2024★ 1 cited

McEval: Massively Multilingual Code Evaluation

Linzheng Chai, Shukai Liu, Jian Yang +15

Code large language models (LLMs) have shown remarkable advances in code understanding, completion, and generation tasks. Programming benchmarks, comprised of a selection of code c…

cs.CL2024

Towards Real-world Scenario: Imbalanced New Intent Discovery

Shun Zhang, Chaoran Yan, Jian Yang +5

New Intent Discovery (NID) aims at detecting known and previously undefined categories of user intent by utilizing limited labeled and massive unlabeled data. Most prior works ofte…

cs.CR2024★ 5 cited

SEvenLLM: Benchmarking, Eliciting, and Enhancing Abilities of Large Language Models in Cyber Threat Intelligence

Hangyuan Ji, Jian Yang, Linzheng Chai +9

To address the increasing complexity and frequency of cybersecurity incidents emphasized by the recent cybersecurity threat reports with over 10 billion instances, cyber threat int…

cs.CL2024

XFormParser: A Simple and Effective Multimodal Multilingual Semi-structured Form Parser

Xianfu Cheng, Hang Zhang, Jian Yang +9

In the domain of Document AI, parsing semi-structured image form is a crucial Key Information Extraction (KIE) task. The advent of pre-trained multimodal models significantly empow…

cs.CL2024★ 1 cited

RoNID: New Intent Discovery with Generated-Reliable Labels and Cluster-friendly Representations

Shun Zhang, Chaoran Yan, Jian Yang +4

New Intent Discovery (NID) strives to identify known and reasonably deduce novel intent groups in the open-world scenario. But current methods face issues with inaccurate pseudo-la…

cs.MA2024★ 1 cited

mABC: multi-Agent Blockchain-Inspired Collaboration for root cause analysis in micro-services architecture

Wei Zhang, Hongcheng Guo, Jian Yang +8

Root cause analysis (RCA) in Micro-services architecture (MSA) with escalating complexity encounters complex challenges in maintaining system stability and efficiency due to fault…

cs.CL2024

New Intent Discovery with Attracting and Dispersing Prototype

Shun Zhang, Jian Yang, Jiaqi Bai +4

New Intent Discovery (NID) aims to recognize known and infer new intent categories with the help of limited labeled and large-scale unlabeled data. The task is addressed as a featu…

cs.CL2023★ 1 cited

Multilingual Entity and Relation Extraction from Unified to Language-specific Training

Zixiang Wang, Jian Yang, Tongliang Li +5

Entity and relation extraction is a key task in information extraction, where the output can be used for downstream NLP tasks. Existing approaches for entity and relation extractio…