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Solving Zebra Puzzles Using Constraint-Guided Multi-Agent Systems

https://arxiv.org/html/2407.03956v3
We also introduce an automated grid puzzle grader to assess the correctness of our puzzle solutions and show that the automated grader is reliable by evaluating it in a user-study

Report GitHub Issue

https://arxiv.org/html/2608.00785v1
com Abstract Content discovery systems depend on relevance judgment for search quality evaluation, but human annotation faces inter-annotator disagreement and scaling costs

Very Large-Scale Multi-Agent Simulation in AgentScope

https://arxiv.org/html/2407.17789v2
The source code is released on GitHub111https://github

1 Introduction

https://arxiv.org/html/2403.08299v1
The landscape of software development has witnessed a paradigm shift with the advent of AI-powered assistants, exemplified by GitHub Copilot

Underspecification in Language Modeling Tasks: A Causality-Informed

https://arxiv.org/html/2210.00131v4
Code and open-source demos available at https://github

1 Introduction

https://arxiv.org/html/2407.02518v2
com Abstract Large language models (LLMs) for code are typically trained to align with natural language instructions to closely follow their intentions and requirements

1 Introduction

https://arxiv.org/html/2506.01844v1
2 Related work Vision-language models (VLMs). Vision-language-action models (VLAs). 3 SmolVLA: small, efficient and capable Overview. 3.1 Model architecture Vision-language model (VLM). State, action, and feature projectors. Visual

Software Engineering

https://arxiv.org/list/cs.SE/new
Through an analysis of 1,966 open source projects, 1,355 Github issues, 444 CVE reports, and 361 StackOverflow posts, we systematically map the feature support and real-world usage of globs across six common ecosystems that utilize globs