Natural Language Processing
Natural Language Processing (NLP) focuses on enabling computers to understand, interpret, and generate human language. Current research heavily emphasizes large language models (LLMs), exploring their capabilities in various tasks like question answering, text classification, and translation, while also addressing challenges such as bias, efficiency, and the need for better evaluation metrics. The field's significance lies in its potential to revolutionize numerous applications, from improving healthcare and education to enhancing information access and facilitating more effective human-computer interaction.
Papers
Controllable Text Generation for Large Language Models: A Survey
Xun Liang, Hanyu Wang, Yezhaohui Wang, Shichao Song, Jiawei Yang, Simin Niu, Jie Hu, Dan Liu, Shunyu Yao, Feiyu Xiong, Zhiyu Li
The Russian-focused embedders' exploration: ruMTEB benchmark and Russian embedding model design
Artem Snegirev, Maria Tikhonova, Anna Maksimova, Alena Fenogenova, Alexander Abramov
Implicit Sentiment Analysis Based on Chain of Thought Prompting
Zhihua Duan, Jialin Wang
WeQA: A Benchmark for Retrieval Augmented Generation in Wind Energy Domain
Rounak Meyur, Hung Phan, Sridevi Wagle, Jan Strube, Mahantesh Halappanavar, Sameera Horawalavithana, Anurag Acharya, Sai Munikoti
Clinical Context-aware Radiology Report Generation from Medical Images using Transformers
Sonit Singh
RedWhale: An Adapted Korean LLM Through Efficient Continual Pretraining
Anh-Dung Vo, Minseong Jung, Wonbeen Lee, Daewoo Choi
Inside the Black Box: Detecting Data Leakage in Pre-trained Language Encoders
Yuan Xin, Zheng Li, Ning Yu, Dingfan Chen, Mario Fritz, Michael Backes, Yang Zhang
NLP for The Greek Language: A Longer Survey
Katerina Papantoniou, Yannis Tzitzikas
Language Modeling on Tabular Data: A Survey of Foundations, Techniques and Evolution
Yucheng Ruan, Xiang Lan, Jingying Ma, Yizhi Dong, Kai He, Mengling Feng
CyberPal.AI: Empowering LLMs with Expert-Driven Cybersecurity Instructions
Matan Levi, Yair Alluouche, Daniel Ohayon, Anton Puzanov
ConVerSum: A Contrastive Learning-based Approach for Data-Scarce Solution of Cross-Lingual Summarization Beyond Direct Equivalents
Sanzana Karim Lora, M. Sohel Rahman, Rifat Shahriyar
Research on color recipe recommendation based on unstructured data using TENN
Seongsu Jhang, Donghwi Yoo, Jaeyong Kown
Risks and NLP Design: A Case Study on Procedural Document QA
Nikita Haduong, Alice Gao, Noah A. Smith
Quantifying the Effectiveness of Student Organization Activities using Natural Language Processing
Lyberius Ennio F. Taruc, Arvin R. De La Cruz
Understanding Enthymemes in Argument Maps: Bridging Argument Mining and Logic-based Argumentation
Jonathan Ben-Naim, Victor David, Anthony Hunter