Papers
SAFETY-J: Evaluating Safety with Critique
Yixiu Liu, Yuxiang Zheng, Shijie Xia et al.
Sailor: Open Language Models for South-East Asia
Longxu Dou, Qian Liu, Guangtao Zeng et al.
Salient Information Prompting to Steer Content in Prompt-based Abstractive Summarization
Lei Xu, Mohammed Asad Karim, Saket Dingliwal et al.
SALMON: A Structure-Aware Language Model with logicality and densification strategy for Temporal Knowledge Graph Reasoning
Fu Zhang, Jinghao Lin, Jingwei Cheng
SambaLingo: Teaching Large Language Models New Languages
Zoltan Csaki, Bo Li, Jonathan Lingjie Li et al.
Sample Design Engineering: An Empirical Study on Designing Better Fine-Tuning Samples for Information Extraction with LLMs
Biyang Guo, He Wang, Wenyilin Xiao et al.
Samsung R&D Institute Philippines @ WMT 2024 Indic MT Task
Matthew Theodore Roque, Carlos Rafael Catalan, Dan John Velasco et al.
Samsung R&D Institute Philippines @ WMT 2024 Low-resource Languages of Spain Shared Task
Dan John Velasco, Manuel Antonio Rufino, Jan Christian Blaise Cruz
Sanitizing Large Language Models in Bug Detection with Data-Flow
Chengpeng Wang, Wuqi Zhang, Zian Su et al.
SARCAT: Generative Span-Act Guided Response Generation using Copy-enhanced Target Augmentation
Jeong-Doo Lee, Hyeongjun Choi, Beomseok Hong et al.
SaSR-Net: Source-Aware Semantic Representation Network for Enhancing Audio-Visual Question Answering
Tianyu Yang, Yiyang Nan, Lisen Dai et al.
Satyrn: A Platform for Analytics Augmented Generation
Marko Sterbentz, Cameron Barrie, Shubham Shahi et al.
SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales
Tianyang Xu, Shujin Wu, Shizhe Diao et al.
Scalable and Domain-General Abstractive Proposition Segmentation
Mohammad Javad Hosseini, Yang Gao, Tim Baumgärtner et al.
Scalable Data Ablation Approximations for Language Models through Modular Training and Merging
Clara Na, Ian Magnusson, Ananya Harsh Jha et al.
Scalable Efficient Training of Large Language Models with Low-dimensional Projected Attention
Xingtai Lv, Ning Ding, Kaiyan Zhang et al.
Scalable Fine-tuning from Multiple Data Sources: A First-Order Approximation Approach
Dongyue Li, Ziniu Zhang, Lu Wang et al.
ScaleLLM: A Resource-Frugal LLM Serving Framework by Optimizing End-to-End Efficiency
Yuhang Yao, Han Jin, Alay Dilipbhai Shah et al.
ScalingFilter: Assessing Data Quality through Inverse Utilization of Scaling Laws
Ruihang Li, Yixuan Wei, Miaosen Zhang et al.
Scaling Laws Across Model Architectures: A Comparative Analysis of Dense and MoE Models in Large Language Models
Siqi Wang, Zhengyu Chen, Bei Li et al.
Scaling Laws for Fact Memorization of Large Language Models
Xingyu Lu, Xiaonan Li, Qinyuan Cheng et al.
Scaling Laws for Linear Complexity Language Models
Xuyang Shen, Dong Li, Ruitao Leng et al.
Scaling Laws of Decoder-Only Models on the Multilingual Machine Translation Task
Gaëtan Caillaut, Mariam Nakhlé, Raheel Qader et al.
Scaling Parameter-Constrained Language Models with Quality Data
Ernie Chang, Matteo Paltenghi, Yang Li et al.
Scaling Properties of Speech Language Models
Santiago Cuervo, Ricard Marxer