惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

人人都是产品经理
人人都是产品经理
量子位
博客园 - 三生石上(FineUI控件)
博客园 - Franky
博客园_首页
罗磊的独立博客
酷 壳 – CoolShell
酷 壳 – CoolShell
G
Google Developers Blog
IT之家
IT之家
Google DeepMind News
Google DeepMind News
爱范儿
爱范儿
Last Week in AI
Last Week in AI
U
Unit 42
J
Java Code Geeks
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
MyScale Blog
MyScale Blog
H
Help Net Security
V
V2EX
S
SegmentFault 最新的问题
月光博客
月光博客
Martin Fowler
Martin Fowler
Vercel News
Vercel News
Y
Y Combinator Blog
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More

Paper Index on ACL Anthology

A Bounded Coordination-Support Capability for Multi-Party Settings: Task-State Monitoring in Firefighter Incident Command A Dataset of Latin Etymologies Extracted from Wiktionary An Efficient Approach for Answering Not Readily Attainable Questions for RAG-based Applications Automated German Alt Text Generation for News Charts Call Support Copilot: A Reproducible Multimodal System for Speech Emotion Recognition, Intent Understanding, and Agent Assistance Can Large Language Models Replace Statistical Software? Code-Switching Detection in Multilingual Child Speech with SwissBERT Concept Extraction and Webb’s Depth of Knowledge: Comparing LLM Question Generation Pipelines for Educational Assessment Data Augmentation for Historical NER: A Systematic Comparison of Lexical and LLM-based Approaches Enhancing Retrieval via Cognitively Motivated Document Expansion Extending the Contact Hypothesis: Cross-Linguistic Evaluation of Religion and Nationality Bias When Prompting LLMs in German and Icelandic Extracting Article-Level Legal Dependencies from Swiss Federal Law using LLMs How Good is AI on Swiss Voting Booklets? A Multilingual OCR and Alignment Benchmark Optimizing Large Language Models for Robust Domain-Specific Text-to-SQL: From Prompting to Preference Alignment Proceedings of the 11th Edition of the Swiss Text Analytics Conference Reinforcement Learning for Latent-Space Thinking in LLMs RUMLEM: A Dictionary-Based Lemmatizer for Romansh Skill Extraction from Resumes and Job Offers across Six Languages Text vs. Phoneme Intermediates for Low-Resource Swiss German The Same Email, Signed Differently: Testing Negotiation Bias and Recommendation Stability in LLMs Which Skills Debate Reaches the Public? Comparing Scientific Literature and Media Coverage of AI and LLM Skill Impacts (2022–2025) Controlling Language and Style of Multi-lingual Generative Language Models with Control Vectors Hybrid Human-LLM Corpus Construction and LLM Evaluation for the Caused-Motion Construction Implicit and Indirect: Detecting Face-threatening and Paired Actions in Asynchronous Online Conversations Northern European Journal of Language Technology, Volume 11 A modular architecture for creating multimodal embodied agents with an episodic Knowledge Graph as an explainable and controllable long-term memory A Neural Approach to Discourse Relation Signal Detection An Analysis of Japanese Sentence-final Particle Yone: Compare Yone and Ne in Response Attribution and the discourse structure of reports Automatic Detection of the Bulgarian Evidential Renarrative
AntIF:大语言模型抗干扰能力评估
2026-03-23 · via Paper Index on ACL Anthology

Abstract

"本文提出了一种多智能体协同的干扰数据生成框架,旨在评测分析大语言模型在复杂干扰下的鲁棒性。该框架以数学领域为起点,逐步扩展至医学、法律、科学及通用场景,构建了涵盖拼写干扰、数字干扰、类型干扰与谣言干扰四类干扰的跨领域数据集AntIF,共计近5000条数据。在此基础上,本文对主流开源语言模型进行了系统的抗干扰能力评估,并结合不同的提示工程策略与模型微调方法,深入分析了AntIF 在提升模型鲁棒性方面的实际效果。"

Anthology ID:
2025.ccl-1.26
Volume:
Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025)
Month:
August
Year:
2025
Address:
Jinan, China
Editors:
Maosong Sun, Peiyong Duan, Zhiyuan Liu, Ruifeng Xu, Weiwei Sun
Venue:
CCL
SIG:
Publisher:
Chinese Information Processing Society of China
Note:
Pages:
335–362
Language:
URL:
https://aclanthology.org/2025.ccl-1.26/
DOI:
Bibkey:
Cite (ACL):
Yajing Luo, Yutao Hou, Yun Chen, and Guanhua Chen. 2025. AntIF:大语言模型抗干扰能力评估. In Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025), pages 335–362, Jinan, China. Chinese Information Processing Society of China.
Cite (Informal):
AntIF:大语言模型抗干扰能力评估 (Luo et al., CCL 2025)
Copy Citation:
PDF:
https://aclanthology.org/2025.ccl-1.26.pdf