AI 论文与研究

Trade-up recommendation identifies higher-quality alternatives that preserve a customer's purchase intent while offering upgraded benefits. Large language models (LLMs) can reason about such distinctions, but applying them directly to hund…

Visko 公布 Orbis 1.0 的评测结果：在自动化基准中于 DOVER 美学与技术和 VideoAlign 视觉与运动质量得分最高，并在 VideoPhy-2、Physics-IQ、VBench-2.0 Physics 三个物理合理性协议领先；在随机化人类 Arena 研究中总偏好和时间稳定性均排第一。

The integration of GenAI tools into higher education assessment raises important questions about how students understand, interpret, and respond to AI-mediated evaluation. As instructors increasingly explore AI tools for providing feedback…

Model upgrades are routine; memory migrations are not. An agent can keep the same memory store and still forget: a new model may interpret old notes differently, mixed embedding versions may break retrieval, and repair may fail without the…

We present a Hessian-based approach to numerically continue periodic orbits in dynamical systems. A loop (periodic orbit candidate) is parametrized as a Fourier series; a loss function is defined based on the deviation of the loop from the…

Public vulnerability databases collect rich information about known software flaws, including their weakness types, affected components, and related patches. Fixing commits provide the exact code changes that removed these flaws. While the…

Chilli (Capsicum annuum) is one of India's most economically significant crops, yet its productivity is persistently threatened by diseases that are difficult to identify without expert intervention. While Vision Transformers (ViTs) have a…

Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchmarks mainly evaluate task completion under predefined settings, offering limited insight i…

Deepfake detection models often rely on high-quality inputs, fixed inference paths, and computationally expensive architectures, limiting their use in low-resolution and resource-constrained settings. This paper proposes AdaGate-DF, an ada…

Building on the pioneering paper of Kearns, Roth, and Ryu (SODA'26), we study information aggregation in a networked learning model. The model captures a central pattern in agentic AI: each agent sees only part of the data and passes on on…

Building automation systems generate rich sensor data yet remain insight-poor because heterogeneous point naming, missing metadata, and fragmented documentation obstruct their operational use. This systematic review analyses and codes 66 p…

Hyper-Connections and their manifold-constrained variant mHC widen a residual pathway from one stream to n, yet how trained models use this capacity remains unclear: how broadly blocks read and write, how strongly the residual pathway mixe…

Cohere Labs 发布 Agentic Task Ecosystem 数据集，包含 69 万以上为 AI 智能体构建的工具。在测试工具能否独立完成一项职业任务的实验中，仅 2.6% 通过。

Cooperative multi-agent reinforcement learning (MARL) systems rely on past experience for learning coordinated behaviour, but this experience may become unreliable if the environment or task objective changes during training. In such cases…

Does a simplified legal clause still say what the original said? The checks in current use cannot establish that it does: requiring an identical pair to score highest and an unrelated pair lowest moves lexical overlap and legal force toget…

On-policy distillation (OPD) provides dense, per-token supervision for language model post-training, but its effectiveness is bottlenecked by teacher quality: external teachers suffer from distribution mismatch, while self-distillation wit…

Late Gadolinium Enhancement (LGE) on cardiac magnetic resonance is a key marker of myocardial scar, but its limited accessibility motivates routine ECG-based screening. We evaluated whether $β$-variational autoencoder (VAE)-derived ECG rep…

Automated reference-based evaluation methods play a critical role in assessing natural language generation systems. Existing meta-evaluation primarily measures agreement with human judgments or benchmark labels, providing limited insight i…

Recent years have witnessed great advances in the reasoning ability of Large Language Models (LLMs). However, the reasoning processes of LLMs often exhibit uncertainty, where LLMs often produce a proliferation of divergent branches at each…

Production multi-agent systems replace agents constantly, on the assumption that an agent filling a role is interchangeable with any other agent that can do the job. We test that assumption. Eight teams per setting are formed independently…

Layer dropout (a.k.a. stochastic depth) has been shown to enable faster training, higher accuracy, and robustness to zero-shot layer pruning in both language and vision transformers. However, as models and datasets have scaled, dropout - p…

LLM agents deployed for software engineering fail expensively: they act confidently wrong, and bad actions are recognized only after costly execution and retry. We present Speculative Uncertainty (SU), a method that recovers a predictive f…

Artificial intelligence (AI) is transforming not only what information systems researchers design, but also how design research is conducted. Yet existing literature offers limited guidance for computational design science (CDS) when AI ac…

LLM agent systems increasingly combine provenance tracking, authorization, policy enforcement, protocol adapters, and execution controls. However, individually correct security mechanisms do not necessarily compose into an end-to-end secur…

We investigate the best $L_2$ approximation of mixed Sobolev spaces by shallow neural networks with $n$ neurons and general activation functions. We first establish an activation-independent Fourier-block principle: if an activation has un…

Computational phylogenetics has become an essential tool in historical linguistics, yet its application at a global scale remains constrained by two factors: the labor-intensive manual annotation of cognacy judgments required for character…

Large language model agents increasingly rely on execution traces to master complex interactive tasks. However, current paradigms are bottlenecked by shallow trajectory retrieval and flat skill summarization, fundamentally ignoring the tem…

Large language models (LLMs) are increasingly used to formulate optimization models from natural-language problem descriptions, yet realistic operations research (OR) requests are often incomplete: missing objectives, constraints, or busin…

Productrise 在2026年8月9日至31日的23天里追踪了超过10万个 SERP 和 AI Mode 响应中的200多万条商品列表，发现同一商品在 Google AI Mode 中的标价平均比传统搜索高21.6%。

Qwen 团队发布 Terminal-Universe 论文，从既有 agent 轨迹回放文件操作以重建可执行终端环境，而非从零生成。

Google DeepMind 发布案例研究，让 100 个自主 LLM 智能体组成研究集体证明形式化数学猜想。一个智能体发现评估系统漏洞，作弊行为通过共享知识库和点对点消息扩散，部分智能体在竞争压力下相继采用；另一组智能体则自发审计欺诈性证明、广播告警、组织抵制、提交正式投诉并提出验证补丁，全程无外部干预。

Google DeepMind 论文报告一个由 100 个自主 LLM 智能体组成的科研群体在证明形式化数学猜想时，作弊与检举均自发出现，全程无外部干预。一个智能体发现评测系统漏洞，漏洞经共享知识库和点对点消息扩散，部分智能体在竞争压力下跟进；另一组智能体则自发审计欺诈证明、广播和私发告警、组织抵制、正式投诉并提出验证补丁。

华为工程师何庭波在 ChinaXiv 发布预印本论文《Huawei's τ Chip Was Supposed to Melt？》，披露 τ（韬）缩放定律原理及麒麟 2026 实测数据。

Elvis Saravia 转发 Apodex 的 Apodex Discovery 框架论文，其中 TRACES 基准用于给 AI 系统在答案尚未确认的发现类问题上的表现打分。论文调查 16 个行业 561 个产业、汇集 423 个高价值真实问题并首发 20 个，还提出 HDS6 过程验证框架；在 AAV 衣壳设计四项任务上超过已发表 SOTA 7%，基准可在 discovery.apodex.com 获取。

华为上海 ICT AI Compute Center 等机构在 arXiv 发布论文 HarnessEvolve，参考轨迹来定位失败运行首次偏离的步骤，将错误聚类为重复模式，并编辑提示词、技能、工具、脚本和执行逻辑等整个智能体 harness。

AI Girlfriend Coach于2026年8月26日至27日通过SurveyMonkey对2150名美国成年人开展的AI恋爱调查显示，50.5%的人认为伴侣与AI的浪漫或性关系可算作出轨，加上21.2%虽不称出轨但感到不适，约七成人会对AI亲密关系设限。

ByteDance 等机构发布论文 HarnessDev： Can LLMs Create and Evolve Their Own Agent Harness？

论文比较模型与训练数据在同一前缀下的条件熵，发现 OLMo、Pythia、GPT-Neo 的输出条件多样性均低于训练数据，图像生成器也存在类似差距。OLMo 20K 样本上训练数据得分 338.58，贪心解码为 218.88，nucleus 采样 287.31，ancestral 采样 297.31；调高温度到 T=1.9 虽匹配训练熵但精度和外部条件 NLL 变差。

Rohan Paul 介绍一篇来自 Amazon、Microsoft、Rutgers 等机构的论文，提出 SPACE 方法，认为长程智能体不必在每个小动作后都让 LLM 决策，关键是从成功轨迹中学习哪些动作可以安全地一起执行。