新闻
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...
Attention Is Not Always the Answer: Optimizing Voice Activity Detection with Simple Feature Fusion
arXiv:2506.01365v1 Announce Type: cross Abstract: Voice Activity Detection (VAD) plays a key role in speech...
Attention Basin: Why Contextual Position Matters in Large Language Models
arXiv:2508.05128v1 Announce Type: new Abstract: The performance of Large Language Models (LLMs) is significantly sensitive...
AsyncSwitch: Asynchronous Text-Speech Adaptation for Code-Switched ASR
arXiv:2506.14190v1 Announce Type: new Abstract: Developing code-switched ASR systems is challenging due to language ambiguity...
AssistedDS: Benchmarking How External Domain Knowledge Assists LLMs in Automated Data Science
arXiv:2506.13992v1 Announce Type: cross Abstract: Large language models (LLMs) have advanced the automation of data...
Assemble Your Crew: Automatic Multi-agent Communication Topology Design via Autoregressive Graph Generation
arXiv:2507.18224v4 Announce Type: replace-cross Abstract: Multi-agent systems (MAS) based on large language models (LLMs) have...
Ask Good Questions for Large Language Models
arXiv:2508.14025v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have significantly improved...
As AI safety concerns mount, three pioneers make the case for staying open
At Ai4, three of the world’s most respected AI experts — Geoffrey Hinton, Fei-Fei Li...
Are Your LLMs Capable of Stable Reasoning?
arXiv:2412.13147v5 Announce Type: replace-cross Abstract: The rapid advancement of large language models (LLMs) has shown...
