新闻
FourierMoE: Fourier Mixture-of-Experts Adaptation of Large Language Models
arXiv:2604.01762v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) has emerged as a crucial paradigm for...
Four things we’d need to put data centers in space
MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to...
Four reasons to be optimistic about AI’s energy usage
The day after his inauguration in January, President Donald Trump announced Stargate, a $500 billion...
Format-Adapter: Improving Reasoning Capability of LLMs by Adapting Suitable Format
arXiv:2506.23133v1 Announce Type: new Abstract: Generating and voting multiple answers is an effective method to...
Forget the hype — real AI agents solve bounded problems, not open-world fantasies
Event-driven multi-agent systems are a practical architecture for working with imperfect tools in a structured...
Forensic deepfake audio detection using segmental speech features
arXiv:2505.13847v1 Announce Type: cross Abstract: This study explores the potential of using acoustic features of...
Forcing LLMs to be evil during training can make them nicer in the long run
A new study from Anthropic suggests that traits such as sycophancy or evilness are associated...
FMBench: Adaptive Large Language Model Output Formatting
arXiv:2602.06384v1 Announce Type: new Abstract: Producing outputs that satisfy both semantic intent and format constraints...
FLUX.1 Kontext enables in-context image generation for enterprise AI pipelines
FLUX.1 Kontext from Black Forest Labs aims to let users edit images multiple times through...
FluoroSAM: A Language-promptable Foundation Model for Flexible X-ray Image Segmentation
arXiv:2403.08059v3 Announce Type: replace-cross Abstract: Language promptable X-ray image segmentation would enable greater flexibility for...
Five Years of SciCap: What We Learned and Future Directions for Scientific Figure Captioning
arXiv:2512.21789v1 Announce Type: new Abstract: Between 2021 and 2025, the SciCap project grew from a...
FIT: Defying Catastrophic Forgetting in Continual LLM Unlearning
arXiv:2601.21682v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate impressive capabilities across diverse tasks...
