arXiv AI
Jul 23
EvoDRC: A Self-Evolving Agentic Framework for Automated DRC Violation Repair
arXiv:2607. 20019v1 Announce Type: new Abstract: Design rule check (DRC) closure remains a major bottleneck in advanced-node physical design.
DRC-Aid: Design-Rule Correction via Agentic Framework utilizing Inference-Time Large Language Models
arXiv:2607. 22761v1 Announce Type: cross Abstract: Resolving Design Rule Violations (DRVs) in layouts entails an iterative loop of geometric edits and verification.
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arXiv AI
Jul 15
Multi-Perspective Agentic Program Repair via Code Property Graphs and Temporal Execution Graphs
arXiv:2607. 12605v1 Announce Type: cross Abstract: Large language models (LLMs) have improved automated program repair (APR), but two limitations remain.
arXiv AI
Jul 22
Bridging the Last Mile of Circuit Design: PostEDA-Bench, a Hierarchical Benchmark for PPA Convergence and DRC Fixing
arXiv:2605. 06936v3 Announce Type: replace-cross Abstract: LLM-based agents are increasingly applied to the "last mile" of Electronic Design Automation (EDA): repairing residual sign-off Design Rule Check (DRC) violations and converging Power-Performance-Area (PPA) targets after tool runs.
arXiv Machine Learning
Jun 5
CASS-RTL: Correctness-Aware Subspace Steering for RTL Generation with LLMs
arXiv:2606. 05680v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have enabled the automatic synthesis (generation) of register-transfer level (RTL) code from natural language instructions, offering a promising pathway to accelerate chip design.
arXiv Machine Learning
Jun 25
Polaris: A G\"odel Agent Framework for Small Language Models through Experience-Abstracted Policy Repair
arXiv:2603. 23129v4 Announce Type: replace Abstract: G\"odel agent realize recursive self-improvement: an agent inspects its own policy and traces and then modifies that policy in a tested loop.
arXiv Machine Learning
Jun 24
Polaris: A Godel Agent Framework for Small Language Models through Experience-Abstracted Policy Repair
arXiv:2603. 23129v3 Announce Type: replace Abstract: G\"odel agent realize recursive self-improvement: an agent inspects its own policy and traces and then modifies that policy in a tested loop.
arXiv AI
Aug 5
TraceCAD: Trace-Guided Repair for Agentic CAD Generation
arXiv:2608. 03062v1 Announce Type: new Abstract: LLM-based CAD agents produce executable parametric programs, but their correction loops may lose evidence about satisfied requirements, faulty operations, and prior repairs.
arXiv AI
Jul 14
Agentic Skill Optimization over Lie Algebroids
arXiv:2607. 11493v1 Announce Type: cross Abstract: Agentic systems increasingly improve themselves by editing skills: prompts, rubrics, plans, tool contracts, examples, validators, and traces.
arXiv AI
Jun 10
Constructing coherent spatial memory in LLM agents through graph rectification
arXiv:2510. 04195v2 Announce Type: replace Abstract: Given a map description through global traversal navigation instructions, an LLM can often infer the implicit spatial layout and answer user queries by providing shortest paths.
arXiv AI
Aug 10
ADIAS: Automated Design of Interactive Agentic Systems
arXiv:2608. 06410v1 Announce Type: new Abstract: Automated agent design improves agent harnesses through iterative revision, evaluation, and feedback summarization.
arXiv AI
22h ago
LLM-Only PDDL Domain Repair with Open-Weight Models
arXiv:2608. 17341v1 Announce Type: new Abstract: AI planning is concerned with finding a sequence of actions that achieves a specified goal.
Hugging Face Trending Papers
Jul 13
Agentic Skill Optimization over Lie Algebroids
Agentic systems increasingly improve themselves by editing skills: prompts, rubrics, plans, tool contracts, examples, validators, and traces. Skill edits are not independent coordinates in a vector space: they are local repairs to structured artifacts whose effects are observed only after rollout, validation, and critique.