Search Results for author:
Found 23 papers, 8 papers with code
DeBackdoor: A Deductive Framework for Detecting Backdoor Attacks on Deep Models with Limited Data
In this paper, we consider a practical scenario where a developer obtains a deep model from a third party and uses it as part of a safety-critical system.
Domain-specific Guided Summarization for Mental Health Posts
In domain-specific contexts, particularly mental health, abstractive summarization requires advanced techniques adept at handling specialized content to generate domain-relevant and faithful summaries.
Prompting Video-Language Foundation Models with Domain-specific Fine-grained Heuristics for Video Question Answering
Video Question Answering (VideoQA) represents a crucial intersection between video understanding and language processing, requiring both discriminative unimodal comprehension and sophisticated cross-modal interaction for accurate inference.
Multi-granularity Contrastive Cross-modal Collaborative Generation for End-to-End Long-term Video Question Answering
Long-term Video Question Answering (VideoQA) is a challenging vision-and-language bridging task focusing on semantic understanding of untrimmed long-term videos and diverse free-form questions, simultaneously emphasizing comprehensive cross-modal reasoning to yield precise answers.
Gemma 2: Improving Open Language Models at a Practical Size
In this work, we introduce Gemma 2, a new addition to the Gemma family of lightweight, state-of-the-art open models, ranging in scale from 2 billion to 27 billion parameters.
Large Language Models for Cyber Security: A Systematic Literature Review
Overall, our survey provides a comprehensive overview of the current state-of-the-art in LLM4Security and identifies several promising directions for future research.
A Comprehensive Survey of 3D Dense Captioning: Localizing and Describing Objects in 3D Scenes
Three-Dimensional (3D) dense captioning is an emerging vision-language bridging task that aims to generate multiple detailed and accurate descriptions for 3D scenes.
CPSDBench: A Large Language Model Evaluation Benchmark and Baseline for Chinese Public Security Domain
Large Language Models (LLMs) have demonstrated significant potential and effectiveness across multiple application domains.
Intelligent Computing: The Latest Advances, Challenges and Future
In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications.
GIDN: A Lightweight Graph Inception Diffusion Network for High-efficient Link Prediction
In this paper, we propose a Graph Inception Diffusion Networks(GIDN) model.
Ranked #1 on
Link Property Prediction
on ogbl-ddi
Ten Years after ImageNet: A 360° Perspective on AI
The rise of attention networks, self-supervised learning, generative modeling, and graph neural networks has widened the application space of AI.
Finding MNEMON: Reviving Memories of Node Embeddings
Previous security research efforts orbiting around graphs have been exclusively focusing on either (de-)anonymizing the graphs or understanding the security and privacy issues of graph neural networks.
Permutation-Invariant Subgraph Discovery
PSPI can be viewed as a robust formulation of the permutation inference or graph matching, where the objective is to find a permutation between two graphs under the assumption that a set of edges may have undergone a perturbation due to an underlying cause.
Log representation as an interface for log processing applications
Log files are files that record events, messages, or transactions.
Time-Window Group-Correlation Support vs. Individual Features: A Detection of Abnormal Users
Autoencoder-based anomaly detection methods have been used in identifying anomalous users from large-scale enterprise logs with the assumption that adversarial activities do not follow past habitual patterns.
Spatial-Temporal Alignment Network for Action Recognition and Detection
The experimental results show that the STAN model can consistently improve the state of the arts in both action detection and action recognition tasks.
Method and Dataset Entity Mining in Scientific Literature: A CNN + Bi-LSTM Model with Self-attention
We finally apply our model on PAKDD papers published from 2009-2019 to mine insightful results from scientific papers published in a longer time span.
Macroscopic nonlocal entanglement generation of two hybrid massive magnon systems
We investigate dynamical generation of macroscopic nonlocal entanglements between two remote massive magnon-superconducting-circuit hybrid systems.
Quantum Physics
The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction
The first contribution is a new dataset, created in a realistic 3D simulator, which is based on real world trajectory data, and then extrapolated by human annotators to achieve different latent goals.
Ranked #1 on
Multi-future Trajectory Prediction
on ForkingPaths
Quantum Unsupervised and Supervised Learning on Superconducting Processors
Machine learning algorithms perform well on identifying patterns in many different datasets due to their versatility.
ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering
It is both crucial and natural to extend this research direction to the video domain for video question answering (VideoQA).
Ranked #31 on
Video Question Answering
on ActivityNet-QA
Visual Question Answering (VQA)
Zero-Shot Video Question Answer
On Exploring Undetermined Relationships for Visual Relationship Detection
In this paper, we explore the beneficial effect of undetermined relationships on visual relationship detection.
