Trending Research
Packing Input Frame Context in Next-Frame Prediction Models for Video Generation
We present a neural network structure, FramePack, to train next-frame (or next-frame-section) prediction models for video generation.
DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting
First, we design a Temporal Clustering Module (TCM) that clusters time series into fine-grained distributions to handle heterogeneous temporal patterns.
SuperEdit: Rectifying and Facilitating Supervision for Instruction-Based Image Editing
This includes rectifying the editing instructions to better align with the original-edited image pairs and using contrastive editing instructions to further enhance their effectiveness.
Zep: A Temporal Knowledge Graph Architecture for Agent Memory
We introduce Zep, a novel memory layer service for AI agents that outperforms the current state-of-the-art system, MemGPT, in the Deep Memory Retrieval (DMR) benchmark.
VGGT: Visual Geometry Grounded Transformer
We present VGGT, a feed-forward neural network that directly infers all key 3D attributes of a scene, including camera parameters, point maps, depth maps, and 3D point tracks, from one, a few, or hundreds of its views.
Step1X-Edit: A Practical Framework for General Image Editing
In recent years, image editing models have witnessed remarkable and rapid development.
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated reasoning, robust perception, and versatile action across diverse domains.
Ranked #1 on
Continual Learning
on AIDS
(using extra training data)
Multi-Modality Representation Learning for Antibody-Antigen Interactions Prediction
While deep learning models play a crucial role in predicting antibody-antigen interactions (AAI), the scarcity of publicly available sequence-structure pairings constrains their generalization.
RM-R1: Reward Modeling as Reasoning
rm-r1-uiuc/rm-r1
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In this work, we introduce a new class of generative reward models -- Reasoning Reward Models (ReasRMs) -- which formulate reward modeling as a reasoning task.
Qwen2.5 Technical Report
qwenlm/qwen2.5
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In addition, for hosted solutions, the proprietary models currently include two mixture-of-experts (MoE) variants: Qwen2. 5-Turbo and Qwen2. 5-Plus, both available from Alibaba Cloud Model Studio.
Ranked #7 on
on GPQA
