Trends · 研究趋势
数据来自 Hugging Face 论文的 AI 提取关键词,按月统计研究方向的增长与热度。
Ailin Huang, Ang Li, Aobo Kong +212 authors
Step 3.5 Flash is a sparse Mixture-of-Experts model that achieves frontier-level agentic intelligence through efficient parameter utilization and optimized attention mechanisms, demonstrating strong performance across multiple benchmarks.
An Yang, Baosong Yang, Binyuan Hui +55 authors
The Qwen2 series, comprising 0.5 to 72 billion parameter models, surpasses prior open models across language understanding, generation, multilingualism, coding, math, and reasoning, with exceptional performance in benchmarks like MMLU, GPQA, HumanEval, GSM8K, BBH, MT-Bench, Arena-Hard, and LiveCodeBench.
Chengpeng Li, Mingfeng Xue, Zhenru Zhang +7 authors
START integrates external tools into large reasoning models to enhance capabilities, using techniques like Hint-infer and Hint Rejection Sampling Fine-Tuning, achieving high performance across various benchmarks.
Yubo Wang, Jiarong Liang, Yuxuan Zhang +5 authors
Function-aware fill-in-the-middle mid-training on code improves coding-agent tool integration and mitigates capability erosion from agentic post-training.
Tiwei Bie, Maosong Cao, Xiang Cao +47 authors
LLaDA2.1 introduces a novel token-to-token editing approach with speed and quality modes, enhanced through reinforcement learning for improved reasoning and instruction following in large language diffusion models.
Dacheng Li, Shiyi Cao, Chengkun Cao +6 authors
A hybrid test-time scaling framework improves code generation coverage and accuracy across various models and domains.
Chris, Yichen Wei, Yi Peng +10 authors
Skywork R1V2 enhances multimodal reasoning through a hybrid reinforcement learning approach that balances reward-model guidance and rule-based strategies, improving training efficiency with the Selective Sample Buffer mechanism and mitigating visual hallucinations.
Etash Guha, Ryan Marten, Sedrick Keh +47 authors
The OpenThoughts project created open-source datasets leading to reasoning models that match or exceed state-of-the-art benchmarks in math, code, and science.
Shanghaoran Quan, Jiaxi Yang, Bowen Yu +14 authors
CodeElo is a standardized code generation benchmark based on CodeForces contests, providing comprehensive evaluation of LLMs' coding abilities with reliable Elo ratings.
Yejie Wang, Keqing He, Dayuan Fu +11 authors
XCoder, a family of models fine-tuned from LLaMA3, achieves state-of-the-art performance on code instruction tasks using a novel data pruning strategy that addresses data leakage and quality in training datasets.
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