Actualités
AutoSpec: An Agentic Framework for Automatically Drafting Patent Specification
arXiv:2509.19640v1 Announce Type: new Abstract: Patents play a critical role in driving technological innovation by...
AutoSDT: Scaling Data-Driven Discovery Tasks Toward Open Co-Scientists
arXiv:2506.08140v1 Announce Type: cross Abstract: Despite long-standing efforts in accelerating scientific discovery with AI, building...
AutoRev: Multi-Modal Graph Retrieval for Automated Peer-Review Generation
arXiv:2505.14376v2 Announce Type: replace Abstract: Enhancing the quality and efficiency of academic publishing is critical...
AutoMixer: Checkpoint Artifacts as Automatic Data Mixers
arXiv:2506.21910v1 Announce Type: new Abstract: In language model training, it is desirable to equip models...
Automatically assessing oral narratives of Afrikaans and isiXhosa children
arXiv:2507.13205v1 Announce Type: new Abstract: Developing narrative and comprehension skills in early childhood is critical...
Automatic Prompt Optimization with Prompt Distillation
arXiv:2508.18992v2 Announce Type: replace Abstract: Autoprompting is the process of automatically selecting optimized prompts for...
Automatic Detection of Inauthentic Templated Responses in English Language Assessments
arXiv:2509.08355v1 Announce Type: new Abstract: In high-stakes English Language Assessments, low-skill test takers may employ...
Automated Generation of Research Workflows from Academic Papers: A Full-text Mining Framework
arXiv:2509.12955v2 Announce Type: replace Abstract: The automated generation of research workflows is essential for improving...
AutoLibra: Agent Metric Induction from Open-Ended Feedback
arXiv:2505.02820v2 Announce Type: replace-cross Abstract: Agents are predominantly evaluated and optimized via task success metrics...
AutoJudge: Judge Decoding Without Manual Annotation
arXiv:2504.20039v4 Announce Type: replace Abstract: We introduce AutoJudge, a method that accelerates large language model...
AutoCode: A New AI Framework that Lets LLMs Create and Verify Competitive Programming Problems, Mirroring the Workflow of Human Problem Setters
Are your LLM code benchmarks actually rejecting wrong-complexity solutions and interactive-protocol violations, or are they...
Audio Contrastive-based Fine-tuning: Decoupling Representation Learning and Classification
arXiv:2309.11895v4 Announce Type: replace-cross Abstract: Standard fine-tuning of pre-trained audio models couples representation learning with...
