Trending Research
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
The challenge is that information entropy may be a suboptimal compression metric: (i) it only leverages unidirectional context and may fail to capture all essential information needed for prompt compression; (ii) it is not aligned with the prompt compression objective.
Graphic Design with Large Multimodal Model
One existing practice is Graphic Layout Generation (GLG), which aims to layout sequential design elements.
Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
facebookresearch/generative-recommenders
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Large-scale recommendation systems are characterized by their reliance on high cardinality, heterogeneous features and the need to handle tens of billions of user actions on a daily basis.
Ranked #1 on
Recommendation Systems
on MovieLens 20M
(HR@10 (full corpus) metric)
Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings
In the realm of security applications, biometric authentication systems play a crucial role, yet one often encounters challenges concerning privacy and security while developing one.
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study
macaronlin/llama3-quantization
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This exploration holds the potential to unveil new insights and challenges for low-bit quantization of LLaMA3 and other forthcoming LLMs, especially in addressing performance degradation problems that suffer in LLM compression.
GhostFaceNets: Lightweight Face Recognition Model From Cheap Operations
The development of deep learning-based biometric models that can be deployed on devices with constrained memory and computational resources has proven to be a significant challenge.
Ranked #1 on
Face Recognition
on CFP-FF
Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization
We show that SAMMO generalizes previous methods and improves the performance of complex prompts on (1) instruction tuning, (2) RAG pipeline tuning, and (3) prompt compression, across several different LLMs.
SpaceByte: Towards Deleting Tokenization from Large Language Modeling
kjslag/spacebyte
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Tokenization is widely used in large language models because it significantly improves performance.
Champ: Controllable and Consistent Human Image Animation with 3D Parametric Guidance
fudan-generative-vision/champ
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In this study, we introduce a methodology for human image animation by leveraging a 3D human parametric model within a latent diffusion framework to enhance shape alignment and motion guidance in curernt human generative techniques.
Arc2Face: A Foundation Model of Human Faces
This paper presents Arc2Face, an identity-conditioned face foundation model, which, given the ArcFace embedding of a person, can generate diverse photo-realistic images with an unparalleled degree of face similarity than existing models.
Ranked #1 on
Diffusion Personalization Tuning Free
on AgeDB
