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Found 23 papers, 12 papers with code
Augmentation, Retrieval, Generation: Event Sequence Prediction with a Three-Stage Sequence-to-Sequence Approach
Currently existing approach models this task as a statistical induction problem, to predict a sequence of events by exploring the similarity between the given goal and the known sequences of events.
CogKGE: A Knowledge Graph Embedding Toolkit and Benchmark for Representing Multi-source and Heterogeneous Knowledge
Designing CogKGE aims to provide a unified programming framework for KGE tasks and a series of knowledge representations for downstream tasks.
Set Generation Networks for End-to-End Knowledge Base Population
In this paper, we formulate end-to-end KBP as a direct set generation problem, avoiding considering the order of multiple facts.
LINKED: Eliciting, Filtering and Integrating Knowledge in Large Language Model for Commonsense Reasoning
In it, we design a reward model to filter out the noisy knowledge and take the marginal consistent reasoning module to reduce invalid reasoning.
Extracting polygonal footprints in off-nadir images with Segment Anything Model
Building Footprint Extraction (BFE) from off-nadir aerial images often involves roof segmentation and offset prediction to adjust roof boundaries to the building footprint.
Multi-modal Crowd Counting via Modal Emulation
To overcome the gap between different modalities, we propose a modal emulation-based two-pass multi-modal crowd-counting framework that enables efficient modal emulation, alignment, and fusion.
Multi-modal Crowd Counting via a Broker Modality
Multi-modal crowd counting involves estimating crowd density from both visual and thermal/depth images.
RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models
Large language models (LLMs) inevitably memorize sensitive, copyrighted, and harmful knowledge from the training corpus; therefore, it is crucial to erase this knowledge from the models.
Brainstorming Brings Power to Large Language Models of Knowledge Reasoning
Large Language Models (LLMs) have demonstrated amazing capabilities in language generation, text comprehension, and knowledge reasoning.
Adaptive Federated Learning Over the Air
In contrast, an Adam-like algorithm converges at the $\mathcal{O}( 1/T )$ rate, demonstrating its advantage in expediting the model training process.
AgentsCourt: Building Judicial Decision-Making Agents with Court Debate Simulation and Legal Knowledge Augmentation
With the development of deep learning, natural language processing technology has effectively improved the efficiency of various aspects of the traditional judicial industry.
Focus on Your Question! Interpreting and Mitigating Toxic CoT Problems in Commonsense Reasoning
Large language models exhibit high-level commonsense reasoning abilities, especially with enhancement methods like Chain-of-Thought (CoT).
DTP-Net: Learning to Reconstruct EEG signals in Time-Frequency Domain by Multi-scale Feature Reuse
Finally, a Decoder layer is employed to reconstruct the artifact-reduced EEG signal.
An Improved Frequent Directions Algorithm for Low-Rank Approximation via Block Krylov Iteration
Frequent Directions, as a deterministic matrix sketching technique, has been proposed for tackling low-rank approximation problems.
Effective Streaming Low-tubal-rank Tensor Approximation via Frequent Directions
Low-tubal-rank tensor approximation has been proposed to analyze large-scale and multi-dimensional data.
CogIE: An Information Extraction Toolkit for Bridging Texts and CogNet
CogNet is a knowledge base that integrates three types of knowledge: linguistic knowledge, world knowledge and commonsense knowledge.
RGB Stream Is Enough for Temporal Action Detection
State-of-the-art temporal action detectors to date are based on two-stream input including RGB frames and optical flow.
Ranked #27 on
Temporal Action Localization
on THUMOS’14
Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report
Video super-resolution has recently become one of the most important mobile-related problems due to the rise of video communication and streaming services.
Multi-Robot Task Allocation -- Complexity and Approximation
Multi-robot task allocation is one of the most fundamental classes of problems in robotics and is crucial for various real-world robotic applications such as search, rescue and area exploration.
CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge
In this paper, we present CogNet, a knowledge base (KB) dedicated to integrating three types of knowledge: (1) linguistic knowledge from FrameNet, which schematically describes situations, objects and events.
TinaFace: Strong but Simple Baseline for Face Detection
Face detection has received intensive attention in recent years.
Ranked #1 on
Occluded Face Detection
on WIDER Face (Hard)
Multi-Grained Spatio-temporal Modeling for Lip-reading
By making full use of the information from different levels in a unified framework, the model is not only able to distinguish words with similar pronunciations, but also becomes robust to appearance changes.
Ranked #21 on
Lipreading
on Lip Reading in the Wild
LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild
It has shown a large variation in this benchmark in several aspects, including the number of samples in each class, video resolution, lighting conditions, and speakers' attributes such as pose, age, gender, and make-up.
Ranked #2 on
Lipreading
on LRW-1000
