Papers Avg
“Avg” 태그가 달린 논문 117편 · 필터 해제
DuET: Dual Incremental Object Detection via Exemplar-Free Task Arithmetic
Real-world object detection systems, such as those in autonomous driving and surveillance, must continuously learn new object categories and simultaneously adapt to changing environmental conditions. Existing approaches,…
Autonomous DrivingAvgClass-Incremental Object DetectionExemplar-Free+5FinBERT2: A Specialized Bidirectional Encoder for Bridging the Gap in Finance-Specific Deployment of Large Language Models
In natural language processing (NLP), the focus has shifted from encoder-only tiny language models like BERT to decoder-only large language models(LLMs) such as GPT-3. However, LLMs' practical application in the financia…
AvgRAGRetrievalRetrieval-augmented Generation+1Deep Modeling and Optimization of Medical Image Classification
Deep models, such as convolutional neural networks (CNNs) and vision transformer (ViT), demonstrate remarkable performance in image classification. However, those deep models require large data to fine-tune, which is imp…
AvgClassificationFederated Learningimage-classification+3ScaleLong: A Multi-Timescale Benchmark for Long Video Understanding
Although long-video understanding demands that models capture hierarchical temporal information -- from clip (seconds) and shot (tens of seconds) to event (minutes) and story (hours) -- existing benchmarks either neglect…
AvgVideo UnderstandingGeoLLaVA-8K: Scaling Remote-Sensing Multimodal Large Language Models to 8K Resolution
Ultra-high-resolution (UHR) remote sensing (RS) imagery offers valuable data for Earth observation but pose challenges for existing multimodal foundation models due to two key bottlenecks: (1) limited availability of UHR…
8kAvgEarth ObservationLarge Language Model+2Spiking Transformers Need High Frequency Information
Spiking Transformers offer an energy-efficient alternative to conventional deep learning by transmitting information solely through binary (0/1) spikes. However, there remains a substantial performance gap compared to ar…
AvgSFDLA: Source-Free Document Layout Analysis
Document Layout Analysis (DLA) is a fundamental task in document understanding. However, existing DLA and adaptation methods often require access to large-scale source data and target labels. This requirements severely l…
AvgDocument Layout Analysisdocument understandingCoreset Spectral Clustering
Coresets have become an invaluable tool for solving $k$-means and kernel $k$-means clustering problems on large datasets with small numbers of clusters. On the other hand, spectral clustering works well on sparse graphs …
AvgClusteringPDX: A Data Layout for Vector Similarity Search
We propose Partition Dimensions Across (PDX), a data layout for vectors (e.g., embeddings) that, similar to PAX [6], stores multiple vectors in one block, using a vertical layout for the dimensions (Figure 1). PDX accele…
AvgAVG-DICE: Stationary Distribution Correction by Regression
Off-policy policy evaluation (OPE), an essential component of reinforcement learning, has long suffered from stationary state distribution mismatch, undermining both stability and accuracy of OPE estimates. While existin…
AvgMuJoCoregressionMoment of Untruth: Dealing with Negative Queries in Video Moment Retrieval
Video Moment Retrieval is a common task to evaluate the performance of visual-language models - it involves localising start and end times of moments in videos from query sentences. The current task formulation assumes t…
AvgMoment RetrievalRetrievalAdapting Biomedical Abstracts into Plain language using Large Language Models
A vast amount of medical knowledge is available for public use through online health forums, and question-answering platforms on social media. The majority of the population in the United States doesn't have the right am…
AvgQuestion AnsweringMulti-modal Fusion and Query Refinement Network for Video Moment Retrieval and Highlight Detection
Given a video and a linguistic query, video moment retrieval and highlight detection (MR&HD) aim to locate all the relevant spans while simultaneously predicting saliency scores. Most existing methods utilize RGB images …
AvgHighlight DetectionMoment RetrievalOptical Flow Estimation+2Prediction Model of Aqua Fisheries Using IoT Devices
Aquaculture involves cultivating marine and freshwater organisms, with real-time monitoring of aquatic parameters being crucial in fish farming. This thesis proposes an IoT-based framework using sensors and Arduino for e…
AvgmodelPredictionMeta-evaluating stability measures: MAX-Senstivity & AVG-Sensitivity
The use of eXplainable Artificial Intelligence (XAI) systems has introduced a set of challenges that need resolution. The XAI robustness, or stability, has been one of the goals of the community from its beginning. Multi…
AvgExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)SensitivityUnsupervised Named Entity Disambiguation for Low Resource Domains
In the ever-evolving landscape of natural language processing and information retrieval, the need for robust and domain-specific entity linking algorithms has become increasingly apparent. It is crucial in a considerable…
AvgEntity DisambiguationEntity LinkingInformation RetrievalEgoPoints: Advancing Point Tracking for Egocentric Videos
We introduce EgoPoints, a benchmark for point tracking in egocentric videos. We annotate 4.7K challenging tracks in egocentric sequences. Compared to the popular TAP-Vid-DAVIS evaluation benchmark, we include 9x more poi…
AvgPoint TrackingPLD+: Accelerating LLM inference by leveraging Language Model Artifacts
To reduce the latency associated with autoretrogressive LLM inference, speculative decoding has emerged as a novel decoding paradigm, where future tokens are drafted and verified in parallel. However, the practical deplo…
AttributeAvgLanguage ModelingLanguage ModellingRectified Flow For Structure Based Drug Design
Deep generative models have achieved tremendous success in structure-based drug design in recent years, especially for generating 3D ligand molecules that bind to specific protein pocket. Notably, diffusion models have t…
AvgDiversityDrug DesignDeep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers
Modern deep policy gradient methods achieve effective performance on simulated robotic tasks, but they all require large replay buffers or expensive batch updates, or both, making them incompatible for real systems with …
AvgDeep Reinforcement LearningIncremental LearningPolicy Gradient Methods