Zinan Lin
Senior Researcher
新闻与深度文章
| Chengquan Guo , Yuzhou Nie, Chulin Xie, Zinan Lin, Wenbo Guo, 和 Bo Li
BlueCodeAgent is an end-to-end blue-teaming framework built to boost code security using automated red-teaming processes, data, and safety rules to guide LLMs’ defensive decisions. Dynamic testing reduces false positives in vulnerability detection.
| Chengquan Guo , Chulin Xie, Yu Yang, Zhaorun Chen, Zinan Lin, Xander Davies, Yarin Gal, Dawn Song, 和 Bo Li
Code agents help streamline software development workflows, but may also introduce critical security risks. Learn how RedCodeAgent automates and improves “red-teaming” attack simulations to help uncover real-world threats that other methods overlook.
Learn what’s next for AI at Research Forum on Sept. 3; WizardArena simulates human-annotated chatbot games; MInference speeds pre-filling for long-context LLMs via dynamic sparse attention; Reef: Fast succinct non-interactive zero-knowledge regex proofs.
| Gbola Afonja, Robert Sim, Zinan Lin, Huseyin Atahan Inan, 和 Sergey Yekhanin
Synthetic data could potentially help address some privacy concerns with AI model development and training, but it comes with limitations. Researchers at Microsoft are exploring techniques for producing more realistic data with strong privacy protections.
新闻报道 | TheSequence
Edge 371: Two-Step LLM Reasoning with Skeleton of Thoughts
Created by Microsoft Research, the technique models some of the aspects of human cognitive reasoning in LLMs. The Skeleton-of-Thoughts (SoT) technique, a recent innovation in the field of Large Language Models (LLMs), represents a significant shift in how these models…
| Zinan Lin, Jinyu Li, Bhaskar Mitra, Siân Lindley, Liang Wang, Nan Yang, 和 Furu Wei
Mixture-of-linear-experts for long-term time series forecasting; Weakly-supervised streaming multilingual speech model with truly zero-shot capability; KBFormer: Diffusion model for structured entity completion; Identifying risks of AI-mediated data access:
| Xuefei Ning 和 Zinan Lin
This research was accepted by the 2024 International Conference on Learning Representations. Large language models (LLMs) such as LLaMA and OpenAI’s GPT-4 are revolutionizing technology. However, one of the common complaints about LLMs is their speed, or lack thereof. In…
| Boxin Wang, Bo Li, 和 Zinan Lin
This paper received the outstanding benchmarks track paper award during NeurIPS 2023 (opens in new tab). How trustworthy are generative pre-trained transformer (GPT) models? To answer this question, University of Illinois Urbana-Champaign, together with Stanford University, University of California, Berkeley,…