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

WordPress大学
WordPress大学
M
MIT News - Artificial intelligence
MyScale Blog
MyScale Blog
博客园_首页
G
Google Developers Blog
博客园 - 【当耐特】
美团技术团队
博客园 - 聂微东
Stack Overflow Blog
Stack Overflow Blog
Vercel News
Vercel News
小众软件
小众软件
博客园 - 司徒正美
雷峰网
雷峰网
T
Tailwind CSS Blog
V
V2EX
博客园 - 三生石上(FineUI控件)
F
Fortinet All Blogs
罗磊的独立博客
量子位
P
Proofpoint News Feed
Microsoft Azure Blog
Microsoft Azure Blog
月光博客
月光博客
A
About on SuperTechFans
Hugging Face - Blog
Hugging Face - Blog

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
Weighted Pseudorandom Generators for Read-Once Branching ...
[Submitted on 12 Feb 2025 (v1), last revised 10 Jul 2026 (this v · 2025-02-12 · via cs updates on arXiv.org

View PDF HTML (experimental)

Abstract:We study weighted pseudorandom generators (WPRGs) and derandomizations for read-once branching programs (ROBPs). Denote $n$ and $w$ as the length and the width of a ROBP. We have the following results.
For standard ROBPs, we give an explicit $\varepsilon$-WPRG with seed length
$$O\left(\frac{\log n\log (nw)}{\max\left\{1,\log\log w-\log\log n\right\}}+\log w \left(\log\log\log w-\log\log\max\left\{2,\frac{\log w}{\log \frac{n}{\varepsilon}}\right\}\right)+\log\frac{1}{\varepsilon}\right).$$
For permutation ROBPs with unbounded widths and single accept nodes, we give an explicit $\varepsilon$-WPRG with seed length
$$O\left( \log n\left( \log\log n + \sqrt{\log(1/\varepsilon)} \right)+\log(1/\varepsilon)\right). $$
We also give a new Nisan-Zuckerman style derandomization for regular ROBPs with width $w$, length $n = 2^{O(\sqrt{\log w})}$, and multiple accept nodes. We attain optimal space complexity $O(\log w)$ for arbitrary approximation error $\varepsilon = 1/\text{poly} (w)$.
All our results are based on iterative weighted pseudorandom reductions, which can iteratively reduce fooling long ROBPs to fooling short ones.

Submission history

From: Ruiyang Wu [view email]
[v1] Wed, 12 Feb 2025 10:27:18 UTC (39 KB)
[v2] Sun, 25 May 2025 02:41:37 UTC (295 KB)
[v3] Thu, 17 Jul 2025 08:59:20 UTC (111 KB)
[v4] Mon, 21 Jul 2025 13:15:56 UTC (111 KB)
[v5] Fri, 10 Jul 2026 08:44:27 UTC (114 KB)