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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...

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...

FinLMM-R1: Enhancing Financial Reasoning in LMM through Scalable Data and Reward Design

arXiv:2506.13066v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) demonstrate significant cross-modal reasoning capabilities. However...

Fingerprint Vector: Enabling Scalable and Efficient Model Fingerprint Transfer via Vector Addition

arXiv:2409.08846v3 Announce Type: replace-cross Abstract: Backdoor-based fingerprinting has emerged as an effective technique for tracing...

FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language

arXiv:2506.20920v1 Announce Type: new Abstract: Pre-training state-of-the-art large language models (LLMs) requires vast amounts of...

Fine-tuning vs. in-context learning: New research guides better LLM customization for real-world tasks

By combining fine-tuning and in-context learning, you get LLMs that can learn tasks that would...

Finding My Voice: Generative Reconstruction of Disordered Speech for Automated Clinical Evaluation

arXiv:2509.19231v1 Announce Type: cross Abstract: We present ChiReSSD, a speech reconstruction framework that preserves children...

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