惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Y
Y Combinator Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
V
V2EX
博客园 - 三生石上(FineUI控件)
Hugging Face - Blog
Hugging Face - Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
罗磊的独立博客
博客园_首页
量子位
雷峰网
雷峰网
GbyAI
GbyAI
小众软件
小众软件
酷 壳 – CoolShell
酷 壳 – CoolShell
D
DataBreaches.Net
H
Hackread – Cybersecurity News, Data Breaches, AI and More
The Cloudflare Blog
IT之家
IT之家
WordPress大学
WordPress大学
人人都是产品经理
人人都是产品经理
Apple Machine Learning Research
Apple Machine Learning Research
P
Proofpoint News Feed
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
博客园 - 聂微东

cs updates on arXiv.org

Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment Agentic Proving for Program Verification MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Framework Benchmarking Google Embeddings 2 against Open-Source Models for Multilingual Dense Retrieval and RAG Systems Structure-Guided Entity Resolution: Fine-Tuning LLMs for Robust Name Matching in Complex Linguistic Contexts Solving the Aircraft Disassembly Scheduling Problem Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents CP or DP? Why Not Both: A Case Study in the Partial Shop Scheduling Problem Asking For An Old Friend: Diagnosing and Mitigating Temporal Failure Modes in LLM-based Statutory Question Answering EDGE-OPD: Internalizing Privileged Context with Evidence Guided On-Policy Distillation ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction Naturalistic measure of social norms alignment Articulatory strategy as a source of variation in acoustic vowel dynamics When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems EquiSumm : A Gender Bias-Aware Framework for Inclusive Tweet Summarization Metacognition as Reward: Reinforcing LLM Reasoning via Knowledge and Regulation Signals From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning Cultural Adaptation in Large Language Models for Political Discourse Emotion Recognition in Sign Language Conversation ClimateChat-300K: A Multi-Modal Facebook Dataset for Understanding Diverse Perspectives in Climate Communication AraHopeCorpus: Annotation Guidelines and Dataset for Hope Speech in Arabic Social Media Crisis Discourse Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning DART: Semantic Recoverability for Structured Tool Agents Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems Parallel Context Compaction for Long-Horizon LLM Agent Serving
The Rising Dominance of Methods Across Science
[Submitted on 6 Jun 2026 (v1), last revised 4 Jul 2026 (this ver · 2026-06-09 · via cs updates on arXiv.org

View PDF

Abstract:Scientific progress is traditionally narrated through the interplay of theoretical insights and experimental findings. Yet this view of science underplays a third and central pillar of progress: the methods that underlie both conceptual advances and empirical evidence. By analysing more than 3 million articles across science published between 1980 and 2019, we find that science has undergone a fundamental structural transition. The share of papers that primarily contribute new methods-methods papers-has doubled across science over the past four decades, rising universally across disciplines and citation impact levels. Rather than a gradual evolution, this transition marks a pivotal shift beginning in the early 1990s, aligning with the computational revolution and the emergence of data-intensive science. The surge in methodological research is not confined to the most cited, elite publications; it spans the full spectrum of scientific output. These findings reveal a systemic reorientation of the scientific ecosystem where reusable methods increasingly serve as the essential infrastructure of scientific advances, challenging the traditional dichotomy of theory and experimental research. As science becomes increasingly methods-driven, our results call for rethinking how research is evaluated, funded and organised-towards better incentivising method innovations. This is especially the case as expanding AI must be effectively integrated with scientific instruments to realise its full potential.

Submission history

From: Lutz Bornmann Dr. [view email]
[v1] Sat, 6 Jun 2026 06:16:22 UTC (1,964 KB)
[v2] Sat, 4 Jul 2026 05:08:12 UTC (1,611 KB)