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Found 11 papers, 6 papers with code
AgentRE: An Agent-Based Framework for Navigating Complex Information Landscapes in Relation Extraction
The relation extraction (RE) in complex scenarios faces challenges such as diverse relation types and ambiguous relations between entities within a single sentence, leading to the poor performance of pure "text-in, text-out" language models (LMs).
PharmaGPT: Domain-Specific Large Language Models for Bio-Pharmaceutical and Chemistry
Large language models (LLMs) have revolutionized Natural Language Processing (NLP) by minimizing the need for complex feature engineering.
PatentGPT: A Large Language Model for Intellectual Property
In recent years, large language models(LLMs) have attracted significant attention due to their exceptional performance across a multitude of natural language process tasks, and have been widely applied in various fields.
ViT-Calibrator: Decision Stream Calibration for Vision Transformer
In this work, we propose a new paradigm dubbed Decision Stream Calibration that boosts the performance of general Vision Transformers.
Team DETR: Guide Queries as a Professional Team in Detection Transformers
Recent proposed DETR variants have made tremendous progress in various scenarios due to their streamlined processes and remarkable performance.
Residual Degradation Learning Unfolding Framework with Mixing Priors across Spectral and Spatial for Compressive Spectral Imaging
However, in the data subproblem, the used sensing matrix is ill-suited for the real degradation process due to the device errors caused by phase aberration, distortion; in the prior subproblem, it is important to design a suitable model to jointly exploit both spatial and spectral priors.
Comparison Knowledge Translation for Generalizable Image Classification
In this paper, we attempt to build a generalizable framework that emulates the humans' recognition mechanism in the image classification task, hoping to improve the classification performance on unseen categories with the support of annotations of other categories.
SuperAnimal pretrained pose estimation models for behavioral analysis
We illustrate the utility of our models in behavioral classification in mice and gait analysis in horses.
Ranked #1 on
Animal Pose Estimation
on Animal-Pose Dataset
(using extra training data)
Can We Leverage Predictive Uncertainty to Detect Dataset Shift and Adversarial Examples in Android Malware Detection?
Our main findings are: (i) predictive uncertainty indeed helps achieve reliable malware detection in the presence of dataset shift, but cannot cope with adversarial evasion attacks; (ii) approximate Bayesian methods are promising to calibrate and generalize malware detectors to deal with dataset shift, but cannot cope with adversarial evasion attacks; (iii) adversarial evasion attacks can render calibration methods useless, and it is an open problem to quantify the uncertainty associated with the predicted labels of adversarial examples (i. e., it is not effective to use predictive uncertainty to detect adversarial examples).
Evolutionary dynamics in financial markets with heterogeneities in strategies and risk tolerance
For a heterogeneous population, the coexistence of investors with pair pattern strategies and reference point strategies causes the price to have a slow fluctuation around a typical equilibrium point and both a large price fluctuation and a no-trading state are avoided, in which the pair pattern strategies push the system far away from the equilibrium while the reference point strategies pull the system back to the equilibrium.
AliMe KG: Domain Knowledge Graph Construction and Application in E-commerce
Pre-sales customer service is of importance to E-commerce platforms as it contributes to optimizing customers' buying process.
