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Found 17 papers, 8 papers with code
Counting-Stars: A Simple, Efficient, and Reasonable Strategy for Evaluating Long-Context Large Language Models
While recent research endeavors have concentrated on developing Large Language Models (LLMs) with robust long-context capabilities, due to the lack of appropriate evaluation strategies, relatively little is known about how well the long-context capability and performance of leading LLMs (e. g., GPT-4 Turbo and Kimi Chat).
Memory efficient location recommendation through proximity-aware representation
Sequential location recommendation plays a huge role in modern life, which can enhance user experience, bring more profit to businesses and assist in government administration.
Bot or Human? Detecting ChatGPT Imposters with A Single Question
Large language models like ChatGPT have recently demonstrated impressive capabilities in natural language understanding and generation, enabling various applications including translation, essay writing, and chit-chatting.
STOA-VLP: Spatial-Temporal Modeling of Object and Action for Video-Language Pre-training
Although large-scale video-language pre-training models, which usually build a global alignment between the video and the text, have achieved remarkable progress on various downstream tasks, the idea of adopting fine-grained information during the pre-training stage is not well explored.
Consistent Style Transfer
Recently, attentional arbitrary style transfer methods have been proposed to achieve fine-grained results, which manipulates the point-wise similarity between content and style features for stylization.
StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generation
We introduce a high resolution, 3D-consistent image and shape generation technique which we call StyleSDF.
Data Pricing in Machine Learning Pipelines
We also investigate pricing in the step of collaborative training of machine learning models, and overview pricing machine learning models for end users in the step of machine learning deployment.
Embedded Discriminative Attention Mechanism for Weakly Supervised Semantic Segmentation
In inference, we directly use the activation masks from the DA layer as pseudo-labels for segmentation.
Giant $c$-axis nonlinear anomalous Hall effect in T$_d$-MoTe$_2$ and WTe$_2$
While the anomalous Hall effect can manifest even without an external magnetic field, time reversal symmetry is nonetheless still broken by the internal magnetization of the sample.
Mesoscale and Nanoscale Physics
Roles of the Narrow Electronic Band near the Fermi Level in 1$T$-TaS$_2$-Related Layered Materials
4$H_{\rm b}$-TaS$_2$ is a superconducting compound with alternating 1$T$-TaS$_2$ and 1$H$-TaS$_2$ layers, where the 1$H$-TaS$_2$ layer has weak charge density wave (CDW) pattern and reduces the CDW coupling between the adjacent 1$T$-TaS$_2$ layers.
Mesoscale and Nanoscale Physics Materials Science
RL-CSDia: Representation Learning of Computer Science Diagrams
Another type of diagrams such as from Computer Science is composed of graphics containing complex topologies and relations, and research on this type of diagrams is still blank.
Time-Travel Rephotography
Many historical people were only ever captured by old, faded, black and white photos, that are distorted due to the limitations of early cameras and the passage of time.
Consistent Video Depth Estimation
We present an algorithm for reconstructing dense, geometrically consistent depth for all pixels in a monocular video.
KeystoneDepth: Visualizing History in 3D
This paper introduces the largest and most diverse collection of rectified stereo image pairs to the research community, KeystoneDepth, consisting of tens of thousands of stereographs of historical people, events, objects, and scenes between 1860 and 1963.
Machine Learning Techniques for Brand-Influencer Matchmaking on the Instagram Social Network
The social media revolution has changed the way that brands interact with consumers.
Fast Non-local Stereo Matching based on Hierarchical Disparity Prediction
This is partially because our DTs overcome the extreme greediness of the MST.
Purine: A bi-graph based deep learning framework
In this paper, we introduce a novel deep learning framework, termed Purine.
