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Found 22 papers, 10 papers with code
Tensor-Var: Variational Data Assimilation in Tensor Product Feature Space
In this paper, we propose \textit{Tensor-Var} to address these challenges using kernel Conditional Mean Embedding (CME).
Data-driven modeling and supervisory control system optimization for plug-in hybrid electric vehicles
Learning-based intelligent energy management systems for plug-in hybrid electric vehicles (PHEVs) are crucial for achieving efficient energy utilization.
RaFe: Ranking Feedback Improves Query Rewriting for RAG
As Large Language Models (LLMs) and Retrieval Augmentation Generation (RAG) techniques have evolved, query rewriting has been widely incorporated into the RAG system for downstream tasks like open-domain QA.
Let LLMs Take on the Latest Challenges! A Chinese Dynamic Question Answering Benchmark
To promote the improvement of Chinese LLMs' ability to answer dynamic questions, in this paper, we introduce CDQA, a Chinese Dynamic QA benchmark containing question-answer pairs related to the latest news on the Chinese Internet.
Safe Reinforcement Learning in Tensor Reproducing Kernel Hilbert Space
This paper delves into the problem of safe reinforcement learning (RL) in a partially observable environment with the aim of achieving safe-reachability objectives.
Geo-Encoder: A Chunk-Argument Bi-Encoder Framework for Chinese Geographic Re-Ranking
Chinese geographic re-ranking task aims to find the most relevant addresses among retrieved candidates, which is crucial for location-related services such as navigation maps.
A Real-Time Robust Ecological-Adaptive Cruise Control Strategy for Battery Electric Vehicles
This work addresses the ecological-adaptive cruise control problem for connected electric vehicles by a computationally efficient robust control strategy.
GeoGLUE: A GeoGraphic Language Understanding Evaluation Benchmark
With a fast developing pace of geographic applications, automatable and intelligent models are essential to be designed to handle the large volume of information.
MGeo: Multi-Modal Geographic Pre-Training Method
Single-modal PTMs can barely make use of the important GC and therefore have limited performance.
A Computationally Efficient Robust Model Predictive Control Framework for Ecological Adaptive Cruise Control Strategy of Electric Vehicles
The control objective of the RMPC is to optimise the electric energy efficiency of the ego vehicle with consideration of a bounded model mismatch disturbance subject to satisfaction of physical and safety constraints.
Economic Potential for Hybrid Electric Vehicles in Urban Signal-free Intersections with Decentralized MPC
The development of electric and connected vehicles as well as automated driving technologies are key towards the smart city, with convenient urban mobility and high energy economy performance.
Forging Multiple Training Objectives for Pre-trained Language Models via Meta-Learning
Multiple pre-training objectives fill the vacancy of the understanding capability of single-objective language modeling, which serves the ultimate purpose of pre-trained language models (PrLMs), generalizing well on a mass of scenarios.
A Convex Optimal Control Framework for Autonomous Vehicle Intersection Crossing
Cooperative vehicle management emerges as a promising solution to improve road traffic safety and efficiency.
Optimal Energy Management of Series Hybrid Electric Vehicles with Engine Start-Stop System
The paper first derives two important analytic results: a) analytic EM optimal solutions of fundamental and commonly used series HEV frameworks, and b) proof of optimality of charge sustaining operation in series HEVs.
AISHELL-NER: Named Entity Recognition from Chinese Speech
Named Entity Recognition (NER) from speech is among Spoken Language Understanding (SLU) tasks, aiming to extract semantic information from the speech signal.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Fixed-Time Convergent Distributed Observer Design of Linear Systems: A Kernel-Based Approach
The robust distributed state estimation for a class of continuous-time linear time-invariant systems is achieved by a novel kernel-based distributed observer, which, for the first time, ensures fixed-time convergence properties.
Cyber-Resilient Self-Triggered Distributed Control of Networked Microgrids Against Multi-Layer DoS Attacks
Networked microgrids with high penetration of distributed generators have ubiquitous remote information exchange, which may be exposed to various cyber security threats.
Probing BERT in Hyperbolic Spaces
We introduce a Poincare probe, a structural probe projecting these embeddings into a Poincare subspace with explicitly defined hierarchies.
Hyperbolic Capsule Networks for Multi-Label Classification
Second, Hyperbolic Dynamic Routing (HDR) is introduced to aggregate hyperbolic capsules in a label-aware manner, so that the label-level discriminative information can be preserved along the depth of neural networks.
Label-Specific Document Representation for Multi-Label Text Classification
Multi-label text classification (MLTC) aims to tag most relevant labels for the given document.
Ranked #1 on
Multi-Label Text Classification
on AAPD
Hyperbolic Interaction Model For Hierarchical Multi-Label Classification
The main reason is that the tree-likeness of the hyperbolic space matches the complexity of symbolic data with hierarchical structures.
Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text Classification
Extreme multi-label text classification (XMTC) aims at tagging a document with most relevant labels from an extremely large-scale label set.
Ranked #1 on
Multi-Label Text Classification
on Amazon-12K
