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
博客园_首页
雷峰网
雷峰网
V
V2EX
博客园 - 司徒正美
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
博客园 - Franky
月光博客
月光博客
Hugging Face - Blog
Hugging Face - Blog
WordPress大学
WordPress大学
T
Tailwind CSS Blog
小众软件
小众软件
博客园 - 叶小钗
美团技术团队
酷 壳 – CoolShell
酷 壳 – CoolShell
Apple Machine Learning Research
Apple Machine Learning Research
IT之家
IT之家
MyScale Blog
MyScale Blog
Blog — PlanetScale
Blog — PlanetScale
大猫的无限游戏
大猫的无限游戏
Jina AI
Jina AI
人人都是产品经理
人人都是产品经理
H
Help Net Security
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻

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
Assembly Spaces: Formal Definitions and Fast Methods for ...
[Submitted on 13 Jun 2026] · 2026-06-16 · via cs updates on arXiv.org

View PDF

Abstract:Assembly theory is an experimental and theoretical framework that introduces a metrological approach to detecting life, with potential applications across diverse substrates. Its two central observables are assembly index and copy number. The assembly index is the minimum number of joining operations required to construct an object from its elementary parts; for molecules, it can be measured using mass spectrometry, infrared spectroscopy, and NMR. Copy number is the abundance of a given distinguishable object within a sample. A key empirical result of the theory is that high assembly index combined with high copy number constitutes a signature that cannot arise abiotically, and this has been validated experimentally in application to molecular biosignatures. The foundational theoretical concept underlying these results is the assembly space, which encodes the causal possibilities determinable from observed objects, with the assembly index the shortest path to them given the physical constraints of a given substrate. Here, we provide a generalized formalism to describe assembly spaces and tools for assembly index approximations. We begin by reviewing the applications of assembly theory across molecules, minerals and atmospheres, and then introduce a general, substrate-independent formal definition of assembly spaces and assembly indices. We develop a unified path hierarchy framework to clarify relationships among the various representations of assembly spaces and assembly paths that appear in the literature on molecular assembly. Finally, we show how formal grammar algorithms can be adapted to efficiently bound assembly index calculations and provide clarification on the utility of such approximations, with the goal to increase the accessibility of tools to explore this emerging area for a broader group of researchers across chemistry, biology, and complexity science.

Submission history

From: Sara Walker [view email]
[v1] Sat, 13 Jun 2026 23:01:35 UTC (1,319 KB)