Trending Research
LLMs as Hackers: Autonomous Linux Privilege Escalation Attacks
We explore the intersection of LLMs and penetration testing to gain insight into their capabilities and challenges in the context of privilege escalation.
Wav-KAN: Wavelet Kolmogorov-Arnold Networks
zavareh1/Wav-KAN
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In this paper , we introduce Wav-KAN, an innovative neural network architecture that leverages the Wavelet Kolmogorov-Arnold Networks (Wav-KAN) framework to enhance interpretability and performance.
RLHF Workflow: From Reward Modeling to Online RLHF
RLHFlow/RLHF-Reward-Modeling
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We present the workflow of Online Iterative Reinforcement Learning from Human Feedback (RLHF) in this technical report, which is widely reported to outperform its offline counterpart by a large margin in the recent large language model (LLM) literature.
Internet sentiment exacerbates intraday overtrading, evidence from A-Share market
Additionally, the effect of sentiment on overtrading is observed to be more pronounced among individual investors in large-cap stocks compared to small- and mid-cap stocks.
GaussianObject: Just Taking Four Images to Get A High-Quality 3D Object with Gaussian Splatting
GaussianObject/GaussianObject
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Then we construct a Gaussian repair model based on diffusion models to supplement the omitted object information, where Gaussians are further refined.
4D Panoptic Scene Graph Generation
jingkang50/psg4d
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NeurIPS 2023
To facilitate research in this new area, we build a richly annotated PSG-4D dataset consisting of 3K RGB-D videos with a total of 1M frames, each of which is labeled with 4D panoptic segmentation masks as well as fine-grained, dynamic scene graphs.
UAV-VisLoc: A Large-scale Dataset for UAV Visual Localization
Our dataset includes 6, 742 drone images and 11 satellite maps, with metadata such as latitude, longitude, altitude, and capture date.
Granite Code Models: A Family of Open Foundation Models for Code Intelligence
Increasingly, code LLMs are being integrated into software development environments to improve the productivity of human programmers, and LLM-based agents are beginning to show promise for handling complex tasks autonomously.
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
We design models based off T5-Base and T5-Large to obtain up to 7x increases in pre-training speed with the same computational resources.
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 Amazon-Book
(HR@10 metric)
