LLM generated responses to mitigate the impact of hate speech
Journal ref EMNLP 2024: Findings of the Association for Computational Linguistics
期刊&会议
EMNLP
Conference on Empirical Methods in Natural Language Processing · 会议 · Natural Language Processing
GLEN: Generative Retrieval via Lexical Index Learning
Comments In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023) main conference. 12 pages, 2 figures, 8 tables
TCSinger: Zero-Shot Singing Voice Synthesis with Style Transfer and Multi-Level Style Control
机构 * Zhejiang University, Shanghai AI Laboratory（浙江大学上海人工智能实验室）
Comments Accepted by EMNLP 2024
Journal ref Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 1960-1975
A Hassle-free Algorithm for Private Learning in Practice: Don't Use Tree Aggregation, Use BLTs
机构 * Google（谷歌）
Comments v2: EMNLP camera ready, minor error and typo fix, updated production model launch info; v3: update production model launch info again to reflect the success of "upgrade all existing FL LMs that have previously been launched without DP to be trained with DP" in arxiv:2306.14793
Retrospex: Language Agent Meets Offline Reinforcement Learning Critic
机构 * State Key Laboratory for Novel Software Technology, Nanjing University（新型软件技术国家重点实验室，南京大学） ； Nanjing University School of Artificial Intelligence（南京大学人工智能学院）
Comments 17 pages, Published in EMNLP 2024 (Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing)
Journal ref Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 4650-4666, ACL Anthology, 2024
Social Bias Probing: Fairness Benchmarking for Language Models
机构 * University of Pisa（比萨大学） ； University of Copenhagen（哥本哈根大学）
Journal ref EMNLP 2024: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024, 14653-14671
Exploring the Impact of Corpus Diversity on Financial Pretrained Language Models
机构 * Department of Applied Artificial Intelligence, Hanyang University（应用人工智能系，翰阳大学） ； Division of Computer Science, Hanyang University（计算机科学系，翰阳大学） ； Ramply Inc.（Ramply公司）
Comments Accepted to EMNLP 2023 (Findings)
Large Language Models Are Involuntary Truth-Tellers: Exploiting Fallacy Failure for Jailbreak Attacks
Comments Accepted to the main conference of EMNLP 2024
ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods
Comments Accepted to EMNLP 2024 Main Conference
PIIvot: A Lightweight NLP Anonymization Framework for Question-Anchored Tutoring Dialogues
Comments 6 pages, 2 figures, submitted to EMNLP 2025, for associated dataset, see https://huggingface.co/datasets/Eedi/Question-Anchored-Tutoring-Dialogues-2k
Predicting generalization performance with correctness discriminators
机构 * Department of Language Science and Technology（语言科学与技术系） ； Saarland Informatics Campus（萨尔兰州信息校园） ； Saarland University（萨尔兰大学）
Comments Appeared in Findings of EMNLP 2024
Pretraining Data Detection for Large Language Models: A Divergence-based Calibration Method
机构 * CAS Key Lab of Network Data Science and Technology, ICT, CAS, Beijing, China（中国科学院信息科技研究所网络数据科学与技术重点实验室） ； University of Chinese Academy of Sciences, Beijing, China（中国科学院大学北京校区） ； Zhongguancun Laboratory, Beijing, China（中关村实验室） ； University of Amsterdam, Amsterdam, The Netherlands（阿姆斯特丹大学）
Comments Accepted by EMNLP 2024 main
MMNeuron: Discovering Neuron-Level Domain-Specific Interpretation in Multimodal Large Language Model
机构 * The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州）） ； The Hong Kong University of Science and Technology（香港科学与技术大学） ； Tongji University（同济大学）
Comments Accepted by the Main Conference of Empirical Methods in Natural Language Processing (EMNLP) 2024
Building a Stable Planner: An Extended Finite State Machine Based Planning Module for Mobile GUI Agent
机构 * Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）） ； School of Computer Science & Engineering, South China University of Technology（华南理工大学计算机科学与工程学院）
Comments 10 pages. Submitted to EMNLP 2025
Domain Gating Ensemble Networks for AI-Generated Text Detection
机构 * University of Pennsylvania（宾夕法尼亚大学）
Comments Submitted to EMNLP 2025
The Mystery of the Pathological Path-star Task for Language Models
机构 * University of Toronto（多伦多大学） ； Vector Institute（向量研究所）
Comments EMNLP 2024 Main at https://aclanthology.org/2024.emnlp-main.695/ See 'Language Models, Graph Searching, and Supervision Adulteration: When More Supervision is Less and How to Make More More' for a follow-up work
Inference and Verbalization Functions During In-Context Learning
机构 * Stanford University（斯坦福大学） ； Mila, University of Montreal（蒙特利尔大学米拉实验室）
Comments EMNLP 2024 Findings
Related Work and Citation Text Generation: A Survey
机构 * Department of Computer Science（计算机科学系） ； University of Texas at Dallas（德克萨斯大学达拉斯分校）
Journal ref https://aclanthology.org/2024.emnlp-main.767/
Context-aware Stand-alone Neural Spelling Correction
Comments 8 pages, 5 tables, 1 figure. Findings of the Association for Computational Linguistics: EMNLP 2020
Journal ref https://aclanthology.org/2020.findings-emnlp.37/
Reassessing Graph Linearization for Sequence-to-sequence AMR Parsing: On the Advantages and Limitations of Triple-Based Encoding
机构 * Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG（格拉诺布尔大学、CNRS、格拉诺布尔INP、LIG） ； Emvista（Emvista公司）
Comments published at Insights from Negative Results in NLP (workshop EMNLP 2025)
Improving Few-Shot Cross-Domain Named Entity Recognition by Instruction Tuning a Word-Embedding based Retrieval Augmented Large Language Model
机构 * IIT Kanpur（印度坎普尔理工学院） ； IISc Bangalore（班加罗尔理工学院）
Journal ref Proceedings of the 2024 Conference on EMNLP Industry Track pages 686,696
IM-BERT: Enhancing Robustness of BERT through the Implicit Euler Method
机构 * Department of Artificial Intelligence（人工智能系） ； KT CORPORATION（KT公司） ； VAIV COMAPANY（VAIV公司） ； Chung-Ang University（Chung-Ang大学） ； School of Computer Science and Engineering（计算机科学与工程学院） ； Graduate School of Advanced Imaging Sciences（高级影像科学研究院）
Comments Accepted to EMNLP 2024 Main
FEDKIM: Adaptive Federated Knowledge Injection into Medical Foundation Models
机构 * Pennsylvania State University（宾夕法尼亚州立大学） ； Georgia State University（佐治亚州立大学）
Comments Accepted by EMNLP'24 Main
Boosting Summarization with Normalizing Flows and Aggressive Training
Journal ref Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Singapore. Association for Computational Linguistics
Adaptive BPE Tokenization for Enhanced Vocabulary Adaptation in Finetuning Pretrained Language Models
机构 * Indian Institute of Technology Kharagpur（印度理工学院卡拉格浦分校）
Comments 11 pages. Accepted at EMNLP Findings 2024 (The 2024 Conference on Empirical Methods in Natural Language Processing)
PyThaiNLP: Thai Natural Language Processing in Python
机构 * VISTEC ； PyThaiNLP ； Trinity College Dublin（三一学院都柏林） ； Technische Universität Berlin（柏林技术大学） ； Max Planck School of Cognition（马克斯·普朗克认知学校）
Comments 12 pages, 2 figures, LaTeX; typos corrected, timeline clarified for section 2. In Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023), pages 25-36, Singapore, Singapore. Empirical Methods in Natural Language Processing
Cross-lingual, Character-Level Neural Morphological Tagging
机构 * Department of Computer Science, Johns Hopkins University（约翰霍普金斯大学计算机科学系） ； German Research Center for Artificial Intelligence（德国人工智能研究中心）
Comments Published as a conference paper at EMNLP 2017; Fixed minor typos and cleaned up formatting
Surveying the Dead Minds: Historical-Psychological Text Analysis with Contextualized Construct Representation (CCR) for Classical Chinese
Journal ref Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP)
ToxiCraft: A Novel Framework for Synthetic Generation of Harmful Information
Comments EMNLP 2024
Journal ref In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 16632-16647, Miami, Florida, USA. Association for Computational Linguistics
DL-QAT: Weight-Decomposed Low-Rank Quantization-Aware Training for Large Language Models
Journal ref https://aclanthology.org/2024.emnlp-industry.10/
