Papers Miscellaneous
“Miscellaneous” 태그가 달린 논문 93편 · 필터 해제
MT-Mol:Multi Agent System with Tool-based Reasoning for Molecular Optimization
Large language models (LLMs) have large potential for molecular optimization, as they can gather external chemistry tools and enable collaborative interactions to iteratively refine molecular candidates. However, this po…
MiscellaneousTaming the Titans: A Survey of Efficient LLM Inference Serving
Large Language Models (LLMs) for Generative AI have achieved remarkable progress, evolving into sophisticated and versatile tools widely adopted across various domains and applications. However, the substantial memory ov…
GPUMiscellaneousSchedulingANCHOLIK-NER: A Benchmark Dataset for Bangla Regional Named Entity Recognition
ANCHOLIK-NER is a linguistically diverse dataset for Named Entity Recognition (NER) in Bangla regional dialects, capturing variations across Sylhet, Chittagong, and Barishal. The dataset has around 10,443 sentences, 3,48…
ArticlesInformation RetrievalMachine TranslationMiscellaneous+4Outlier Synthesis via Hamiltonian Monte Carlo for Out-of-Distribution Detection
Out-of-distribution (OOD) detection is crucial for developing trustworthy and reliable machine learning systems. Recent advances in training with auxiliary OOD data demonstrate efficacy in enhancing detection capabilitie…
MiscellaneousOut-of-Distribution DetectionOut of Distribution (OOD) DetectionA Comprehensive Survey on Visual Question Answering Datasets and Algorithms
Visual question answering (VQA) refers to the problem where, given an image and a natural language question about the image, a correct natural language answer has to be generated. A VQA model has to demonstrate both the …
DiagnosticMiscellaneousQuestion AnsweringSurvey+2Efficient Quality Control of Whole Slide Pathology Images with Human-in-the-loop Training
Histopathology whole slide images (WSIs) are being widely used to develop deep learning-based diagnostic solutions, especially for precision oncology. Most of these diagnostic softwares are vulnerable to biases and impur…
Active LearningArtifact DetectionDiagnosticMiscellaneous+2Correntropy-Based Improper Likelihood Model for Robust Electrophysiological Source Imaging
Bayesian learning provides a unified skeleton to solve the electrophysiological source imaging task. From this perspective, existing source imaging algorithms utilize the Gaussian assumption for the observation noise to …
Bayesian InferenceMiscellaneousVariational InferenceArtificial Neural Network and Deep Learning: Fundamentals and Theory
"Artificial Neural Network and Deep Learning: Fundamentals and Theory" offers a comprehensive exploration of the foundational principles and advanced methodologies in neural networks and deep learning. This book begins w…
Bayesian OptimizationDeep LearningDescriptiveGaussian Processes+1ImagiNet: A Multi-Content Benchmark for Synthetic Image Detection
Recent generative models produce images with a level of authenticity that makes them nearly indistinguishable from real photos and artwork. Potential harmful use cases of these models, necessitate the creation of robust …
Contrastive LearningMiscellaneousMisinformationSynthetic Image DetectionDeep Learning Activation Functions: Fixed-Shape, Parametric, Adaptive, Stochastic, Miscellaneous, Non-Standard, Ensemble
In the architecture of deep learning models, inspired by biological neurons, activation functions (AFs) play a pivotal role. They significantly influence the performance of artificial neural networks. By modulating the n…
MiscellaneousRevisiting Adaptive Cellular Recognition Under Domain Shifts: A Contextual Correspondence View
Cellular nuclei recognition serves as a fundamental and essential step in the workflow of digital pathology. However, with disparate source organs and staining procedures among histology image clusters, the scanned tiles…
Domain AdaptationMiscellaneousAutomated Chronotyping from a Daily Calendar using Machine Learning
Chronotype compares individuals' circadian phase to others. It contextualizes mental health risk assessments and detection of social jet lag, which can hamper mental health and cognitive performance. Existing ways of det…
MiscellaneousEdge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence
Recent years have witnessed a thriving growth of computing facilities connected at the network edge, cultivating edge networks as a fundamental infrastructure for supporting miscellaneous intelligent services.Meanwhile, …
Edge-computingGraph LearningGraph Representation LearningMiscellaneous+1Awesome Multi-modal Object Tracking
Multi-modal object tracking (MMOT) is an emerging field that combines data from various modalities, \eg vision (RGB), depth, thermal infrared, event, language and audio, to estimate the state of an arbitrary object in a …
Autonomous DrivingKnowledge DistillationMiscellaneousObject+5D-NLP at SemEval-2024 Task 2: Evaluating Clinical Inference Capabilities of Large Language Models
Large language models (LLMs) have garnered significant attention and widespread usage due to their impressive performance in various tasks. However, they are not without their own set of challenges, including issues such…
MiscellaneousNatural Language InferenceNatural Language UnderstandingTask 2Pre-training on High Definition X-ray Images: An Experimental Study
Existing X-ray based pre-trained vision models are usually conducted on a relatively small-scale dataset (less than 500k samples) with limited resolution (e.g., 224 $\times$ 224). However, the key to the success of self-…
DecoderMiscellaneousEXAMS-V: A Multi-Discipline Multilingual Multimodal Exam Benchmark for Evaluating Vision Language Models
We introduce EXAMS-V, a new challenging multi-discipline multimodal multilingual exam benchmark for evaluating vision language models. It consists of 20,932 multiple-choice questions across 20 school disciplines covering…
MiscellaneousMultiple-choiceDecomposed Meta-Learning for Few-Shot Sequence Labeling
Few-shot sequence labeling is a general problem formulation for many natural language understanding tasks in data-scarcity scenarios, which require models to generalize to new types via only a few labeled examples. Recen…
Entity TypingEvent DetectionFew-shot NERMeta-Learning+8CMNER: A Chinese Multimodal NER Dataset based on Social Media
Multimodal Named Entity Recognition (MNER) is a pivotal task designed to extract named entities from text with the support of pertinent images. Nonetheless, a notable paucity of data for Chinese MNER has considerably imp…
Miscellaneousnamed-entity-recognitionNamed Entity RecognitionNERC-ICL: Contrastive In-context Learning for Information Extraction
There has been increasing interest in exploring the capabilities of advanced large language models (LLMs) in the field of information extraction (IE), specifically focusing on tasks related to named entity recognition (N…
In-Context LearningMiscellaneousnamed-entity-recognitionNamed Entity Recognition+3