8 citations · 28 across the 21 of their papers we have counts for
21 papers
Enhancing Multilingual Reasoning via Steerable Model Merging
Zhuoran Li, Rui Xu, Jian Yang +8
Model merging is an effective technique for composing the capabilities of a multilingual model and a reasoning model. It has achieved promising generalization in multilingual reaso…
FuzzCoder: Byte-level Fuzzing Test via Large Language Model
Liqun Yang, Jian Yang, Chaoren Wei +13
Fuzzing is an important dynamic program analysis technique designed for finding vulnerabilities in complex software. Fuzzing involves presenting a target program with crafted malic…
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…
UniCoder: Scaling Code Large Language Model via Universal Code
Tao Sun, Linzheng Chai, Jian Yang +6
Intermediate reasoning or acting steps have successfully improved large language models (LLMs) for handling various downstream natural language processing (NLP) tasks. When applyin…
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…
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…
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…
ECLIPSE: Semantic Entropy-LCS for Cross-Lingual Industrial Log Parsing
Wei Zhang, Xianfu Cheng, Yi Zhang +8
Log parsing, a vital task for interpreting the vast and complex data produced within software architectures faces significant challenges in the transition from academic benchmarks…
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…
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…
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…
m3P: Towards Multimodal Multilingual Translation with Multimodal Prompt
Jian Yang, Hongcheng Guo, Yuwei Yin +7
Multilingual translation supports multiple translation directions by projecting all languages in a shared space, but the translation quality is undermined by the difference between…
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…
Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging
Wei Zhang, Xiangyuan Guan, Lu Yunhong +5
Logs produced by extensive software systems are integral to monitoring system behaviors. Advanced log analysis facilitates the detection, alerting, and diagnosis of system faults.…
C-ICL: Contrastive In-context Learning for Information Extraction
Ying Mo, Jiahao Liu, Jian Yang +4
There has been increasing interest in exploring the capabilities of advanced large language models (LLMs) in the field of information extraction (IE), specifically focusing on task…
WGAN-AFL: Seed Generation Augmented Fuzzer with Wasserstein-GAN
Liqun Yang, Chunan Li, Yongxin Qiu +5
The importance of addressing security vulnerabilities is indisputable, with software becoming crucial in sectors such as national defense and finance. Consequently, The security is…
MLAD: A Unified Model for Multi-system Log Anomaly Detection
Runqiang Zang, Hongcheng Guo, Jian Yang +6
In spite of the rapid advancements in unsupervised log anomaly detection techniques, the current mainstream models still necessitate specific training for individual system dataset…
xCoT: Cross-lingual Instruction Tuning for Cross-lingual Chain-of-Thought Reasoning
Linzheng Chai, Jian Yang, Tao Sun +8
Chain-of-thought (CoT) has emerged as a powerful technique to elicit reasoning in large language models and improve a variety of downstream tasks. CoT mainly demonstrates excellent…
LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection
Hongcheng Guo, Jian Yang, Jiaheng Liu +7
Log anomaly detection is a key component in the field of artificial intelligence for IT operations (AIOps). Considering log data of variant domains, retraining the whole network fo…
SVIPTR: Fast and Efficient Scene Text Recognition with Vision Permutable Extractor
Xianfu Cheng, Weixiao Zhou, Xiang Li +8
Scene Text Recognition (STR) is an important and challenging upstream task for building structured information databases, that involves recognizing text within images of natural sc…
MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL
Bing Wang, Changyu Ren, Jian Yang +8
Recent LLM-based Text-to-SQL methods usually suffer from significant performance degradation on "huge" databases and complex user questions that require multi-step reasoning. Moreo…