4 papers
VISPA: Pluralistic Alignment via Automatic Value Selection and Activation
Shenyan Zheng, Jiayou Zhong, Anudeex Shetty +3
As large language models are increasingly used in high-stakes domains, it is essential that their outputs reflect not average} human preference, rather range of varying perspective…
BFS-Prover: Scalable Best-First Tree Search for LLM-based Automatic Theorem Proving
Ran Xin, Chenguang Xi, Jie Yang +6
Recent advancements in large language models (LLMs) have spurred growing interest in automatic theorem proving using Lean4, where effective tree search methods are crucial for navi…
Seed-Coder: Let the Code Model Curate Data for Itself
ByteDance Seed, Yuyu Zhang, Jing Su +24
Code data in large language model (LLM) pretraining is recognized crucial not only for code-related tasks but also for enhancing general intelligence of LLMs. Current open-source L…
FullStack Bench: Evaluating LLMs as Full Stack Coders
Bytedance-Seed-Foundation-Code-Team, :, Yao Cheng +53
As the capabilities of code large language models (LLMs) continue to expand, their applications across diverse code intelligence domains are rapidly increasing. However, most exist…