Trending Research
OMG-Seg: Is One Model Good Enough For All Segmentation?
lxtgh/omg-seg
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In this work, we address various segmentation tasks, each traditionally tackled by distinct or partially unified models.
Demystify Mamba in Vision: A Linear Attention Perspective
LeapLabTHU/MLLA
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By exploring the similarities and disparities between the effective Mamba and subpar linear attention Transformer, we provide comprehensive analyses to demystify the key factors behind Mamba's success.
Efficient Guided Generation for Large Language Models
In this article we show how the problem of neural text generation can be constructively reformulated in terms of transitions between the states of a finite-state machine.
Speaker Embedding-aware Neural Diarization for Flexible Number of Speakers with Textual Information
alibaba-damo-academy/FunASR
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In this paper, we reformulate this task as a single-label prediction problem by encoding the multi-speaker labels with power set.
emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation
alibaba-damo-academy/FunASR
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To the best of our knowledge, emotion2vec is the first universal representation model in various emotion-related tasks, filling a gap in the field.
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
MLA guarantees efficient inference through significantly compressing the Key-Value (KV) cache into a latent vector, while DeepSeekMoE enables training strong models at an economical cost through sparse computation.
Instruct-MusicGen: Unlocking Text-to-Music Editing for Music Language Models via Instruction Tuning
ldzhangyx/instruct-MusicGen
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Recent advances in text-to-music editing, which employ text queries to modify music (e. g.\ by changing its style or adjusting instrumental components), present unique challenges and opportunities for AI-assisted music creation.
ViG: Linear-complexity Visual Sequence Learning with Gated Linear Attention
Recently, linear complexity sequence modeling networks have achieved modeling capabilities similar to Vision Transformers on a variety of computer vision tasks, while using fewer FLOPs and less memory.
Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations
epfml/schedules-and-scaling
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Scale has become a main ingredient in obtaining strong machine learning models.
Improving Diffusion Models for Virtual Try-on
yisol/IDM-VTON
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Finally, we present a customization method using a pair of person-garment images, which significantly improves fidelity and authenticity.
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