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arXiv:2407.05116v1 Announce Type: new Abstract: We present a new parser performance prediction (PPP) model using machine translation performance prediction system (MTPPS), statistically independent of any language or parser, relying only on extrinsic and novel features based on textual, link structural, and bracketing tree structural information. This new system, MTPPS-PPP, can predict the performance of any parser in any language and can be useful for estimating the grammatical difficulty when understanding a given text, for setting expectations from parsing output, for parser selection for a specific domain, and for parser combination systems. We obtain SoA results in PPP of bracketing $F_1$…

arXiv:2407.04992v1 Announce Type: new Abstract: Bayesian causal discovery offers the power to quantify epistemic uncertainties among a broad range of structurally diverse causal theories potentially explaining the data, represented in forms of directed acyclic graphs (DAGs). However, existing methods struggle with efficient DAG sampling due to the complex acyclicity constraint. In this study, we propose a scalable Bayesian approach to effectively learn the posterior distribution over causal graphs given observational data thanks to the ability to generate DAGs without explicitly enforcing acyclicity. Specifically, we introduce a novel differentiable DAG sampling method that can generate a valid acyclic causal graph by…

arXiv:2407.04943v1 Announce Type: new Abstract: YOLO is a deep neural network (DNN) model presented for robust real-time object detection following the one-stage inference approach. It outperforms other real-time object detectors in terms of speed and accuracy by a wide margin. Nevertheless, since YOLO is developed upon a DNN backbone with numerous parameters, it will cause excessive memory load, thereby deploying it on memory-constrained devices is a severe challenge in practice. To overcome this limitation, model compression techniques, such as quantizing parameters to lower-precision values, can be adopted. As the most recent version of YOLO, YOLOv7 achieves such state-of-the-art performance in…