提出统一秩分配方法，突破低秩分解压缩LLM的瓶颈，兼顾效率与性能。
arXiv:2606.21847v1 Announce Type: cross Abstract: Low-rank decomposition serves as a promising compression paradigm for large language models, however…
统一多模态潜在扩散模型实现任意模态间的连贯生成，无需配对数据，跨模态生成能力惊艳
arXiv:2606.16408v1 Announce Type: new Abstract: We introduce MUNI, an end-to-end multimodal latent diffusion framework for any-to-any generation that …
LLM多智能体系统缺乏统一框架？这项目开源一站式代码库，终结重复造轮子和不公平对比
arXiv:2505.16988v2 Announce Type: replace-cross Abstract: LLM-based multi-agent systems (MAS) have demonstrated significant potential in enhancing sin…
LLM推理测试时扩展的统一框架，跨越多种推理模式与问题类型实现显著性能提升。
arXiv:2606.06915v1 Announce Type: cross Abstract: Test-time compute (TTC) scaling has emerged as a powerful paradigm for improving large language mode…
提出统一框架让多智能体系统在LLM中进行潜在通信，超越传统token交互，开启全新协作范式。
arXiv:2606.05711v1 Announce Type: new Abstract: Multi-agent systems built on large language models (LLMs) have become a prevailing paradigm for tackli…
致敬经典电影标题，提出一个覆盖所有领域的统一基准测试框架，为AI模型全面评估提供新思路。
arXiv:2606.06462v1 Announce Type: new Abstract: Benchmarks are fundamental for evaluating and advancing LLMs and MLLMs by providing standardized and e…
通过强化学习将RAG与推理统一在一个框架内，开创性地解决了检索增强与逻辑推理的协同难题。
arXiv:2508.06165v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown strong capabilities through two complementary paradi…
为多模态大模型打造的通用代理框架，MUSE统一多种能力，解锁LLM新玩法。
arXiv:2606.03005v1 Announce Type: new Abstract: Despite rapid progress, multimodal large language models (MLLMs) still fail on tasks that humans solve…
跨层子空间耦合统一框架，揭示大模型SVD压缩方法的新极限与潜力
arXiv:2605.30836v1 Announce Type: new Abstract: Recent SVD based compression methods for large language models like SVD LLM and Basis Sharing can be u…
跳出传统解码局限，提出“先推理后约束”统一框架，让大模型输出更精准可控。
arXiv:2601.07525v2 Announce Type: replace-cross Abstract: Natural generation allows Large Language Models (LLMs) to produce free-form responses with r…
深度学习统一框架，为CT不同对比度相位定制虚拟单色图像，提升诊断精准度与成像灵活性
arXiv:2605.29753v1 Announce Type: cross Abstract: Dual-energy CT (DECT) enables virtual monochromatic imaging (VMI) and improved contrast resolution, …
提出统一框架评估LLM智能体能力，破解跨基准测试结果难以比较的难题。
arXiv:2605.27898v1 Announce Type: new Abstract: As LLMs are increasingly deployed as agents, reliable assessment of their agentic capabilities has bec…
Maxtoken框架提出统一方案，突破AI输出长度与能力边界，值得技术研究者关注。
Article URL: https://zenodo.org/records/20360523 Comments URL: https://news.ycombinator.com/item?id=48253125 Points: 1 # Comments: 0
提出统一数据选择框架，为LLM推理任务高效筛选高质量训练数据，显著提升推理能力。
arXiv:2605.22389v1 Announce Type: new Abstract: Effectively training Large Language Models (LLMs) for complex, long-CoT reasoning is often bottlenecke…
探索统一自蒸馏框架UniSD，为大型语言模型的高效优化与性能提升提供新思路。
arXiv:2605.06597v2 Announce Type: replace Abstract: Self-distillation (SD) offers a promising path for adapting large language models (LLMs) without r…
提出统一谱系框架，在线偏好对齐新解法，理论扎实且方法创新。
arXiv:2605.20408v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) effectively aligns Large Language Models (LLMs) with…
一份超越RLHF的统一对齐理论框架，抽象形式化多种对齐算法并揭示内在联系，为AI安全提供新视角。
arXiv:2506.01523v2 Announce Type: replace Abstract: Alignment via reinforcement learning from human feedback (RLHF) has become the dominant paradigm f…
一篇统一SFT、DAgger、离线RL和OPD视角的LLM蒸馏论文，解耦KL与轨迹，为模型优化提供新理论框架。
arXiv:2605.16826v1 Announce Type: new Abstract: Knowledge distillation is central to LLM post-training, yet its design space remains poorly understood…
提出将参数化动作分布视为动作的新型强化学习框架，统一离散、连续与混合动作空间，简化智能体设计。
arXiv:2506.16608v3 Announce Type: replace-cross Abstract: We introduce a novel reinforcement learning (RL) framework that treats parameterized action …
通过条件信息瓶颈将推理中的预算强制统一为压缩问题，揭示推理与信息论的内在联系。
arXiv:2603.08462v2 Announce Type: replace Abstract: \ac{CoT} prompting improves LLM accuracy on complex tasks but often increases token usage and infe…