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Found 26 papers, 2 papers with code
Beyond Single Frames: Can LMMs Comprehend Temporal and Contextual Narratives in Image Sequences?
Our evaluation of $16$ state-of-the-art LMMs, including GPT-4o and Qwen2. 5VL, reveals a significant performance gap compared to human capabilities, particularly in tasks that require reordering shuffled sequential images.
Digital transformation: A systematic review and bibliometric analysis from the corporate finance perspective
We categorize the literature into three areas according to bibliometric clustering: the measurements (qualitative and quantitative), impact factors (internal and external), and the economic consequences (investment, financing, and firm value).
SG-FSM: A Self-Guiding Zero-Shot Prompting Paradigm for Multi-Hop Question Answering Based on Finite State Machine
Large Language Models with chain-of-thought prompting, such as OpenAI-o1, have shown impressive capabilities in natural language inference tasks.
FAST-GSC: Fast and Adaptive Semantic Transmission for Generative Semantic Communication
Aiming to reduce task latency, our communication mechanism enables fast semantic transmission by parallelizing the processes of semantic extraction at the transmitter and inference at the receiver.
FSM: A Finite State Machine Based Zero-Shot Prompting Paradigm for Multi-Hop Question Answering
Large Language Models (LLMs) with chain-of-thought (COT) prompting have demonstrated impressive abilities on simple nature language inference tasks.
Harnessing the Power of AI-Generated Content for Semantic Communication
Recognizing the transformative capabilities of AI-generated content (AIGC) technologies in content generation, this paper explores a pioneering approach by integrating them into SemCom to address the aforementioned challenges.
GRA: Detecting Oriented Objects through Group-wise Rotating and Attention
GRA can adaptively capture fine-grained features of objects with diverse orientations, comprising two key components: Group-wise Rotating and Group-wise Attention.
2023 Low-Power Computer Vision Challenge (LPCVC) Summary
This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC).
Weaver: Foundation Models for Creative Writing
Weaver is pre-trained on a carefully selected corpus that focuses on improving the writing capabilities of large language models.
STAR-RIS-Assisted Privacy Protection in Semantic Communication System
Semantic communication (SemCom) has emerged as a promising architecture in the realm of intelligent communication paradigms.
Keyword-Based Diverse Image Retrieval by Semantics-aware Contrastive Learning and Transformer
On the one hand, standard retrieval systems are usually biased to common semantics and seldom exploit diversity-aware regularization in training, which makes it difficult to promote diversity by post-processing.
Adaptive Rotated Convolution for Rotated Object Detection
In our ARC module, the convolution kernels rotate adaptively to extract object features with varying orientations in different images, and an efficient conditional computation mechanism is introduced to accommodate the large orientation variations of objects within an image.
Ranked #3 on
Oriented Object Detection
on DOTA 1.0
Secure Wireless Transmission for Reconfigurable Intelligent Surface Aided Full Duplex Systems
We aim to maximize the sum secrecy rate of UL and DL users by jointly optimizing the transmit beamforming, receive beamforming and AN covariance matrix at the BS, and passive beamforming at the RIS.
MALICE: Manipulation Attacks on Learned Image ComprEssion
To characterize the robustness of state-of-the-art learned image compression, we mount white-box and black-box attacks.
Reconfigurable Intelligent Surfaces for Energy Efficiency in Full-duplex Communication System
By jointly designing the active beamforming of two multi-antenna sources and passive beamforming of RIS, we aim to maximize the energy efficiency of the system, where extra self-interference cancellation power consumption in FD system is also considered.
Cross Domain Object Detection by Target-Perceived Dual Branch Distillation
It can adaptively enhance source detector to perceive objects in a target image, by leveraging target proposal contexts from iterative cross-attention.
Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection
Specifically, TRKP adopts the teacher-student framework, where the multi-head teacher network is built to extract knowledge from labeled source domains and guide the student network to learn detectors in unlabeled target domain.
Energy Efficiency Maximization of Simultaneous Transmission and Reflection RIS Assisted Full-Duplex Communications
The penalty-based method is used to design passive beamforming at the STAR-RIS.
Simultaneous Transmission and Reflection Reconfigurable Intelligent Surface Assisted Full-Duplex Communications
This work demonstrates the effectiveness of a novel simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) in Full-Duplex (FD) aided communication system.
Performance Analysis and Codebook Design for mmWave Beamforming System with Beam Squint
Beamforming technology is widely used in millimeter wave systems to combat path losses, and beamformers are usually selected from a predefined codebook.
Fast List Decoders for Polarization-Adjusted Convolutional (PAC) Codes
Moreover, fast list decoding with four types of constituent nodes can further reduce decoding latency with negligible performance degradation.
Information Theory Information Theory
Cognitive Representation Learning of Self-Media Online Article Quality
The automatic quality assessment of self-media online articles is an urgent and new issue, which is of great value to the online recommendation and search.
Hierarchical Feature Embedding for Attribute Recognition
Attribute recognition is a crucial but challenging task due to viewpoint changes, illumination variations and appearance diversities, etc.
HSCJN: A Holistic Semantic Constraint Joint Network for Diverse Response Generation
The sequence-to-sequence (Seq2Seq) model generates target words iteratively given the previously observed words during decoding process, which results in the loss of the holistic semantics in the target response and the complete semantic relationship between responses and dialogue histories.
Dynamic Curriculum Learning for Imbalanced Data Classification
Human attribute analysis is a challenging task in the field of computer vision, since the data is largely imbalance-distributed.
Fast and Globally Optimal Rigid Registration of 3D Point Sets by Transformation Decomposition
However, the existing global methods are slow for two main reasons: the computational complexity of BnB is exponential to the problem dimensionality (which is six for 3D rigid registration), and the bound evaluation used in BnB is inefficient.
