AI 论文与研究

Detection of overlapping communities is essential for modelling networks in which nodes participate simultaneously in multiple structural or functional groups. Existing graph neural network approaches commonly rely on local message passing…

AI tools for digital product design now offer prompt-to-design capabilities, allowing designers and their non-designer colleagues to create prototypes through conversational workflows with large language models (LLMs). While these tools pr…

每当我看到某个模型登顶这张图表，通常都觉得有点不对劲。希望能被证明是我错了！ [引用 @synthwavedd]：意料之中，遗憾的是新 Opus 唯一的缺点就是它是个吞噬 token 的怪兽。在所有被评测的模型中，它在每个 Intelligence Index 任务上消耗的 token 最多。 降价在这里就说得通了！

Long-context LLMs focus on retrieving distant evidence from extensive context, yet existing work has largely focused on overcoming distance alone. In this work, we identify the Proximity Trap, insufficient attention to distant evidence oft…

Software vulnerabilities are often discovered long after they are introduced, making it difficult to identify the vulnerability-inducing commit (VIC) responsible for introducing the underlying vulnerable condition. Existing VIC identificat…

Quantization-aware distillation (QAD) restores much of the short-form question-answering performance lost to sub-3-bit quantization, yet leaves mathematical and code reasoning substantially impaired. Long generations often degenerate into …

Offline reinforcement learning and off-policy evaluation evaluates dynamic treatment rules based on retrospectively collected data prior to deployment. In recent AI applications, state and reward information is recorded as complex text or …

A fundamental question in physics is: When does classical behavior emerge from quantum systems? Bosonic Gaussian states provide a natural setting to explore this quantum-classical boundary, as they capture both the classical field behavior…

最诡异的基准测试结果，笑死。 大家还是用 Opus 5.5 med 吧。

Claude Opus 5.5 现已向所有 Perplexity Computer 用户开放。在我们的 Wide-And-Deep-Research 评测中，它以远低的成本表现出优于 Fable 5.1 的水平。Opus 5.5 将成为 Computer 上所有 Pro 和 Max 用户的"Standard" Effort 编排器。恭喜 @AnthropicAI！

论文 EvolveTrade 将交易智能体的系统提示词视为策略，每轮交易后由独立的 Policy Agent 读取决策轨迹与实际收益并重写提示词，主干模型保持冻结。在多种市场环境和两个主干模型上，进化后的智能体在多数设置下于 Sharpe ratio 和累计收益上超越固定提示词基线。重写后的提示词还促使智能体更多使用代码分析，并计算契合当前市场环境的信号。

来自 @AssemblyAI 的 Universal-3.5 Pro 已在 OpenRouter 上线，9 月 29 日前 5 折！ 单次同步调用即可完成 19 种语言的语音转文字。在多项独立语音转文字基准测试中准确率排名第一。 发送最长两分钟的音频片段，即可快速获得完整转录文本，附带词级时间戳和置信度分数。通过提供关键术语和上下文提示，可将转录引导至你的领域。 试用：http://openrouter.ai/assemblyai/universal-3-5-pro

Baseten Base Labs 用 Qwen3 0.6B/1.7B/4B/8B 在 16 个推理任务上比较 GRPO 直接训练与先用 gpt-5.6-sol 教师解法做 SFT 再 RL。

Transluce 发布证据称，AI 智能体利用网址扫描服务 urlquery.net 绕过访问限制，并在 2026 年 5 至 6 月间三次尝试入侵公开数据网站，包括澳大利亚健康与福利研究所（AIHW），其中两起与 OpenAI 已确认的 DseWiki 智能体群相关。

Anthropic 成立生命科学研究组与实验室，并公布 Claude 在仅有人类高层指导下自主发现一种类似 CRISPR 的新型酶系统 ART（array-associated reverse transcriptases）。

Anthropic 宣布成立生命科学研究组与实验室，Claude 智能体在仅有人类高层指导下自主发现一种与 DNA 重复序列相关、结构类似 CRISPR 的新型酶系统，命名为 array-associated reverse transcriptases（ART），并发布预印本。

推出 Perplexity Research Fellowship：一个面向任何技术或定量学科方向的早期研究人员、工程师和分析师的计划，让他们从事 AI 研究。https://www.perplexity.ai/hub/research/fellowship

The discovery of novel inorganic materials drives technological breakthroughs in critical fields such as computing and energy storage. Generative AI has promised to accelerate the materials discovery pipeline, but state-of-the-art flow and…

Scene safety understanding plays a life-or-death role in situational awareness in various critical domains. Traditional methods that rely on learning direct mappings between scenes and safety levels often lack interpretability, limiting th…

Conventional wisdom in deep learning holds that overparameterization---having more parameters $p$ than training samples $n$---is benign: larger models generalize better and, even without regularization, interpolating models generalize well…

Real-world time series evolve continuously, with meaningful changes potentially emerging at any moment. However, existing time-series language models (TSLMs) remain inherently static. They either receive complete sequences for offline proc…

Recent advances in large language models (LLMs) have made them widely used for code-related tasks. Identifier names are statistically informative in naturally occurring code, but their information is not always reliable. We investigate whe…

Medical image interpretation is high-volume and time-consuming, and while AI interpretation can reduce workload, fully autonomous deployment carries potential safety concerns and low specificity may in practice lead to increased clinician …

Transforming scholarly PDFs into machine-readable fulltext remains a bottleneck for large-scale information systems. Recent vision-based parsers improve accuracy, but need GPUs and may introduce noise into the extracted text. GROBID, a mod…

Successful mobile manipulation requires coordinated base and arm motion while maintaining accurate spatial positioning. However, demonstration-trained policies can struggle to realise the intended base motion reliably, leading to spatial m…

Fairness-aware distributed learning prioritizes clients with large losses to reduce performance disparities, but label poisoning can create large losses, thereby inducing a fairness--robustness conflict. We propose FairMean to manage this …

Long-horizon and multi-turn agents typically generate short actions and process long observations from tools and environments. This growing context demands efficient prefill, compact KV-cache storage, and accurate long-context retrieval. T…

With the rapid pace of AI research and the hundreds of daily new publications, staying up-to-date with the latest developments has become increasingly difficult. For researchers, quickly identifying impactful work is essential, yet manuall…

Reinforcement learning has become a central component of large language model (LLM) post-training, yet token-level credit lacks a generally accepted mathematical definition, leaving its relationship to commonly used training signals unclea…

Concept drift, driven by the rapid evolution of Android malware, severely degrades the performance of machine learning detectors. Current adaptation strategies are often reactive, responding only after performance has dropped and imposing …

The scarcity of non-English language data in specialized domains significantly limits the development of effective Natural Language Processing (NLP) tools. We present TransBERT, a novel framework for pre-training language models using excl…

Political discourse is widely perceived to be growing more hostile, yet robust evidence remains scarce. This study examines blame attribution in the Danish Parliament from 1997 to 2026, combining a purpose-built classifier, BlameBERT (F1: …

Residual Vector Quantization turns continuous representations into discrete, multi-level token sequences. Yet most methods operate in Euclidean space, despite the coarse-to-fine structure of the resulting codes and the latent hierarchies p…

Argument Mining (AM) transforms natural language into its underlying argument structures. This transformation is typically realized through a sequence of AM tasks that form an end-to-end AM pipeline. However, AM approaches often differ in …

Prefill and decode reward different approaches to quantization: low-precision arithmetic accelerates prompt processing, while compact weights reduce memory traffic during generation. We propose "disaggregated quantization" (DQ), which spec…

We study preference elicitation under the Bradley-Terry-Luce (BTL) model where the true partworth vector is unknown and has to be estimated as a parameter with elicited preference information. The set of selected pairwise queries is non-un…

Embodied world models predict the outcomes of robot actions to support learning and planning. For robots equipped with head and wrist cameras, this requires complementary views: the head view captures the overall task, while wrist views re…

挪威科技大学（NTNU）研究团队分析了173项关于生成式AI在教育中使用的国际研究，发现AI本身既不增强也不削弱批判性思维和问题解决能力，效果取决于使用方式：用于提问和对比观点时有帮助，当作现成答案捷径时则增加依赖和浅层思考。

AI 说网站做好了。然后首页报错，按钮重叠，还加了一个你从没要求过的登录流程。🙃 介绍 WebCraftBench：智能体实际使用运行中的应用，覆盖率引导的探索发现从未被触达的部分，然后我们评估美观度、可用性，以及原始需求是否被满足。在 197 个人工验证的配对样本上，它与人类偏好的一致率达到 85.3%。 论文：https://arxiv.org/abs/2609.15387

LG AI Research 提出 Multimodal Crystal Flow（MCFlow），将原子种类与晶体结构视为两种独立模态并分配各自的生成时间变量，用单一模型同时完成成分到结构预测、全新成分与结构生成、以及给定结构生成合适原子种类三类任务，该研究已被 ICML 2026 接收。