7 papers
Fine-Tuning Small Language Models for Reliable VASP INCAR Generation
Xinyue Zhang, Jixiang Li, Bin Shao +3
Language models can prepare VASP INCAR files from natural-language requests, but so far only large proprietary cloud models come close to handling the tightly coupled, physics-sens…
Knowledge-Based Pull Requests: A Trusted Workflow for Agent-Mediated Knowledge Collaboration
Xinyu Zhang, Weiwei Sun
AI coding agents are changing the bottleneck in software collaboration: code is increasingly cheap, while understanding intent, negotiating scope, and governing long-term project r…
INCARBench: A Benchmark for Scientific Configuration in VASP INCAR by Large Language Models
Bin Shao, Jixiang Li, Xinyue Zhang +3
Large language models (LLMs) are increasingly being integrated into first-principles computational workflows, yet their ability to configure scientific calculations remains poorly…
Towards Cross-lingual Values Judgment: A Consensus-Pluralism Perspective
Yukun Chen, Xinyu Zhang, Boyi Deng +6
As large language models (LLMs) are employed worldwide, existing evaluation paradigms for their multilingual capabilities primarily focus on factual task performance, neglecting th…
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
DeepSeek-AI, Anyi Xu, Bangcai Lin +315
We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…
Qwen3-TTS Technical Report
Hangrui Hu, Xinfa Zhu, Ting He +13
In this report, we present the Qwen3-TTS series, a family of advanced multilingual, controllable, robust, and streaming text-to-speech models. Qwen3-TTS supports state-of-the-art 3…