Trending Research
Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers
zhentingqi/rstar
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This paper introduces rStar, a self-play mutual reasoning approach that significantly improves reasoning capabilities of small language models (SLMs) without fine-tuning or superior models.
Large Language Model-Based Agents for Software Engineering: A Survey
The recent advance in Large Language Models (LLMs) has shaped a new paradigm of AI agents, i. e., LLM-based agents.
Towards a Unified View of Preference Learning for Large Language Models: A Survey
Finally, based on our unified perspective, we explore the challenges and future research directions for aligning large language models with human preferences.
Docling Technical Report
DS4SD/docling
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This technical report introduces Docling, an easy to use, self-contained, MIT-licensed open-source package for PDF document conversion.
RealisDance: Equip controllable character animation with realistic hands
2) The hands generated using the DWPose sequence are blurry and unrealistic.
RobustSAM: Segment Anything Robustly on Degraded Images
robustsam/RobustSAM
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CVPR 2024
Segment Anything Model (SAM) has emerged as a transformative approach in image segmentation, acclaimed for its robust zero-shot segmentation capabilities and flexible prompting system.
FLUX that Plays Music
feizc/fluxmusic
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This paper explores a simple extension of diffusion-based rectified flow Transformers for text-to-music generation, termed as FluxMusic.
Ranked #2 on
Text-to-Music Generation
on MusicCaps
One-Shot Diffusion Mimicker for Handwritten Text Generation
dailenson/one-dm
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Extensive experiments demonstrate that our method can successfully generate handwriting scripts with just one sample reference in multiple languages, even outperforming previous methods using over ten samples.
The AdEMAMix Optimizer: Better, Faster, Older
nanowell/AdEMAMix-Optimizer-Pytorch
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This work questions the use of a single EMA to accumulate past gradients and empirically demonstrates how this choice can be sub-optimal: a single EMA cannot simultaneously give a high weight to the immediate past, and a non-negligible weight to older gradients.
