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Found 12 papers, 3 papers with code
From Images to Detection: Machine Learning for Blood Pattern Classification
Bloodstain Pattern Analysis (BPA) helps us understand how bloodstains form, with a focus on their size, shape, and distribution.
DSGram: Dynamic Weighting Sub-Metrics for Grammatical Error Correction in the Era of Large Language Models
Evaluating the performance of Grammatical Error Correction (GEC) models has become increasingly challenging, as large language model (LLM)-based GEC systems often produce corrections that diverge from provided gold references.
Optimizing Item-based Marketing Promotion Efficiency in C2C Marketplace with Dynamic Sequential Coupon Allocation Framework
We introduce a Dynamic Sequential Coupon Allocation Framework (DSCAF) to optimize item coupon allocation strategies across a series of promotions.
Stochastic Parrots or ICU Experts? Large Language Models in Critical Care Medicine: A Scoping Review
Peer-reviewed journal and conference articles that discussed the application of LLMs in critical care settings were included.
Fast solution to the fair ranking problem using the Sinkhorn algorithm
In two-sided marketplaces such as online flea markets, recommender systems for providing consumers with personalized item rankings play a key role in promoting transactions between providers and consumers.
Robust portfolio optimization model for electronic coupon allocation
We apply a robust portfolio optimization model based on customer segmentation to the coupon allocation problem.
RulePrompt: Weakly Supervised Text Classification with Prompting PLMs and Self-Iterative Logical Rules
Weakly supervised text classification (WSTC), also called zero-shot or dataless text classification, has attracted increasing attention due to its applicability in classifying a mass of texts within the dynamic and open Web environment, since it requires only a limited set of seed words (label names) for each category instead of labeled data.
Wavelet-Decoupling Contrastive Enhancement Network for Fine-Grained Skeleton-Based Action Recognition
Skeleton-based action recognition has attracted much attention, benefiting from its succinctness and robustness.
NTIRE 2023 Quality Assessment of Video Enhancement Challenge
61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions.
Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation
COREP primarily employs a guided updating mechanism to learn a stable graph representation for the state, termed as causal-origin representation.
Robust Direct Learning for Causal Data Fusion
In the era of big data, the explosive growth of multi-source heterogeneous data offers many exciting challenges and opportunities for improving the inference of conditional average treatment effects.
Personalized Promotion Decision Making Based on Direct and Enduring Effect Predictions
To achieve a better lift return on investment (lift ROI) on the enduring effect of the promotion and improve customer retention and loyalty, we propose a framework of multiple treatment promotion decision making by modeling each customer's direct and enduring response.
