16 citations · 88 across the 40 of their papers we have counts for
41 papers
DECAF: De-Clustering for Adaptive Representational Unlearning
Anjie Le, Can Peng, Hongcheng Guo +1
Machine unlearning, which aims to remove the influence of specific training data from a trained model, is a key requirement for privacy, accountability, and adaptive deployment. We…
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…
H2HTalk: Evaluating Large Language Models as Emotional Companion
Boyang Wang, Yalun Wu, Hongcheng Guo +1
As digital emotional support needs grow, Large Language Model companions offer promising authentic, always-available empathy, though rigorous evaluation lags behind model advanceme…
RedOne: Revealing Domain-specific LLM Post-Training in Social Networking Services
Fei Zhao, Chonggang Lu, Yue Wang +22
As a primary medium for modern information dissemination, social networking services (SNS) have experienced rapid growth, which has proposed significant challenges for platform con…
DinoCompanion: An Attachment-Theory Informed Multimodal Robot for Emotionally Responsive Child-AI Interaction
Boyang Wang, Yuhao Song, Jinyuan Cao +3
Children's emotional development fundamentally relies on secure attachment relationships, yet current AI companions lack the theoretical foundation to provide developmentally appro…
Pet-Bench: Benchmarking the Abilities of Large Language Models as E-Pets in Social Network Services
Hongcheng Guo, Zheyong Xie, Shaosheng Cao +6
As interest in using Large Language Models for interactive and emotionally rich experiences grows, virtual pet companionship emerges as a novel yet underexplored application. Exist…
SNS-Bench-VL: Benchmarking Multimodal Large Language Models in Social Networking Services
Hongcheng Guo, Zheyong Xie, Shaosheng Cao +5
With the increasing integration of visual and textual content in Social Networking Services (SNS), evaluating the multimodal capabilities of Large Language Models (LLMs) is crucial…
U2-BENCH: Benchmarking Large Vision-Language Models on Ultrasound Understanding
Anjie Le, Henan Liu, Yue Wang +18
Ultrasound is a widely-used imaging modality critical to global healthcare, yet its interpretation remains challenging due to its varying image quality on operators, noises, and an…
Redefining Machine Translation on Social Network Services with Large Language Models
Hongcheng Guo, Fei Zhao, Shaosheng Cao +8
The globalization of social interactions has heightened the need for machine translation (MT) on Social Network Services (SNS), yet traditional models struggle with culturally nuan…
Cluster-Driven Expert Pruning for Mixture-of-Experts Large Language Models
Hongcheng Guo, Juntao Yao, Boyang Wang +5
Mixture-of-Experts (MoE) architectures have emerged as a promising paradigm for scaling large language models (LLMs) with sparse activation of task-specific experts. Despite their…
DependEval: Benchmarking LLMs for Repository Dependency Understanding
Junjia Du, Yadi Liu, Hongcheng Guo +4
While large language models (LLMs) have shown considerable promise in code generation, real-world software development demands advanced repository-level reasoning. This includes un…
Mitigating Hallucinations in Large Vision-Language Models by Adaptively Constraining Information Flow
Jiaqi Bai, Hongcheng Guo, Zhongyuan Peng +4
Large vision-language models show tremendous potential in understanding visual information through human languages. However, they are prone to suffer from object hallucination, i.e…
CodeIF: Benchmarking the Instruction-Following Capabilities of Large Language Models for Code Generation
Kaiwen Yan, Hongcheng Guo, Xuanqing Shi +3
With the rapid advancement of Large Language Models (LLMs), the demand for robust instruction-following capabilities in code generation tasks has grown significantly. Code generati…
Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey
Liang Chen, Zekun Wang, Shuhuai Ren +24
Building on the foundations of language modeling in natural language processing, Next Token Prediction (NTP) has evolved into a versatile training objective for machine learning ta…
ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback
Wei Zhang, Yi Zhang, Li Zhu +5
Large Language Models (LLMs) have made significant strides in Natural Language Processing and coding, yet they struggle with robustness and accuracy in complex function calls. To t…
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…
IW-Bench: Evaluating Large Multimodal Models for Converting Image-to-Web
Hongcheng Guo, Wei Zhang, Junhao Chen +9
Recently advancements in large multimodal models have led to significant strides in image comprehension capabilities. Despite these advancements, there is a lack of the robust benc…
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…
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…
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…
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.…