Large Language
Large language models (LLMs) are rapidly advancing artificial intelligence, aiming to create systems capable of understanding and generating human-like text. Current research focuses on improving efficiency (e.g., through speculative decoding), exploring their intriguing properties in multimodal contexts (combining language with vision), and applying them to diverse fields like healthcare, manufacturing, and software engineering. This work is significant because LLMs are already impacting various sectors, offering potential for improved decision-making, automation, and personalized experiences, while also raising important questions about robustness, security, and ethical implications.
Papers
Northeastern Uni at Multilingual Counterspeech Generation: Enhancing Counter Speech Generation with LLM Alignment through Direct Preference Optimization
Sahil Wadhwa, Chengtian Xu, Haoming Chen, Aakash Mahalingam, Akankshya Kar, Divya Chaudhary
ResoFilter: Rine-grained Synthetic Data Filtering for Large Language Models through Data-Parameter Resonance Analysis
Zeao Tu, Xiangdi Meng, Yu He, Zihan Yao, Tianyu Qi, Jun Liu, Ming Li
Analysis and Visualization of Linguistic Structures in Large Language Models: Neural Representations of Verb-Particle Constructions in BERT
Hassane Kissane, Achim Schilling, Patrick Krauss
Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems
Genki Kusano, Kosuke Akimoto, Kunihiro Takeoka
Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Sridhar Thiagarajan, Craig Boutilier, Rishabh Agarwal, Aviral Kumar, Aleksandra Faust
A Survey on Large Language Model-based Agents for Statistics and Data Science
Maojun Sun, Ruijian Han, Binyan Jiang, Houduo Qi, Defeng Sun, Yancheng Yuan, Jian Huang
Towards Efficient and Explainable Hate Speech Detection via Model Distillation
Paloma Piot, Javier Parapar
CharacterBench: Benchmarking Character Customization of Large Language Models
Jinfeng Zhou, Yongkang Huang, Bosi Wen, Guanqun Bi, Yuxuan Chen, Pei Ke, Zhuang Chen, Xiyao Xiao, Libiao Peng, Kuntian Tang, Rongsheng Zhang, Le Zhang, Tangjie Lv, Zhipeng Hu, Hongning Wang, Minlie Huang
Why Does ChatGPT "Delve" So Much? Exploring the Sources of Lexical Overrepresentation in Large Language Models
Tom S. Juzek, Zina B. Ward
CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models
Zhihao Du, Yuxuan Wang, Qian Chen, Xian Shi, Xiang Lv, Tianyu Zhao, Zhifu Gao, Yexin Yang, Changfeng Gao, Hui Wang, Fan Yu, Huadai Liu, Zhengyan Sheng, Yue Gu, Chong Deng, Wen Wang, Shiliang Zhang, Zhijie Yan, Jingren Zhou
NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models
Asmaa Abdallah, Abdullatif Albaseer, Abdulkadir Celik, Mohamed Abdallah, Ahmed M. Eltawil
FDM-Bench: A Comprehensive Benchmark for Evaluating Large Language Models in Additive Manufacturing Tasks
Ahmadreza Eslaminia, Adrian Jackson, Beitong Tian, Avi Stern, Hallie Gordon, Rajiv Malhotra, Klara Nahrstedt, Chenhui Shao
Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models
Neel Jain, Aditya Shrivastava, Chenyang Zhu, Daben Liu, Alfy Samuel, Ashwinee Panda, Anoop Kumar, Micah Goldblum, Tom Goldstein
Towards Controllable Speech Synthesis in the Era of Large Language Models: A Survey
Tianxin Xie, Yan Rong, Pengfei Zhang, Li Liu
Data Quality Enhancement on the Basis of Diversity with Large Language Models for Text Classification: Uncovered, Difficult, and Noisy
Min Zeng, Caiquan Liu, Shiqi Zhang, Li Xie, Chen Sang, Xiaoxin Chen, Xiaoxin Chen