Search Results for author:
Found 39 papers, 4 papers with code
Perception Compressor:A training-free prompt compression method in long context scenarios
Large Language Models (LLMs) demonstrate exceptional capabilities in various scenarios.
IRSC: A Zero-shot Evaluation Benchmark for Information Retrieval through Semantic Comprehension in Retrieval-Augmented Generation Scenarios
In Retrieval-Augmented Generation (RAG) tasks using Large Language Models (LLMs), the quality of retrieved information is critical to the final output.
QAEA-DR: A Unified Text Augmentation Framework for Dense Retrieval
In dense retrieval, embedding long texts into dense vectors can result in information loss, leading to inaccurate query-text matching.
OpenFMNav: Towards Open-Set Zero-Shot Object Navigation via Vision-Language Foundation Models
By leveraging the reasoning and generalizing abilities of foundation models, our method can understand free-form human instructions and perform effective open-set zero-shot navigation in diverse environments.
AAT: Adapting Audio Transformer for Various Acoustics Recognition Tasks
Other fine-tuning methods either struggle to address this issue or fail to achieve matching performance.
Dissipativity-Based Decentralized Co-Design of Distributed Controllers and Communication Topologies for Vehicular Platoons
However, it is beneficial to design both the platooning controller and the communication topology simultaneously, i. e., controller and topology co-design, especially in the cases of platoon splitting and merging.
Time-Frequency Localization Characteristics of the Delay-Doppler Plane Orthogonal Pulse
Furthermore, we determine the TFA for the recently proposed generalized design of the DDOP.
Structural Balance of Complex Weighted Graphs and Multi-partite Consensus
The structural balance of a signed graph is known to be necessary and sufficient to obtain a bipartite consensus among agents with friend-foe relationships.
MSFormer: A Skeleton-multiview Fusion Method For Tooth Instance Segmentation
Furthermore, the segmentation accuracy is improved by 2. 4%-5. 5% with the increasing volume of training data.
Quantum-Enhanced Forecasting: Leveraging Quantum Gramian Angular Field and CNNs for Stock Return Predictions
We propose a time series forecasting method named Quantum Gramian Angular Field (QGAF).
YOLO: An Efficient Terahertz Band Integrated Sensing and Communications Scheme with Beam Squint
Moreover, we propose a supporting method based on extended array signal estimation, which utilizes the phase changes of different frequency subcarriers within different OFDM symbols to estimate the distance and velocity of dynamic targets.
Smooth Robustness Measures for Symbolic Control Via Signal Temporal Logic
Moreover, the degree of satisfaction of STL specifications can be evaluated using ``STL robust semantics'' as a scalar robustness measure.
Decentralized and Compositional Interconnection Topology Synthesis for Linear Networked Systems
In this paper, we consider networked systems comprised of interconnected sets of linear subsystems and propose a decentralized and compositional approach to stabilize or dissipativate such linear networked systems via optimally modifying some existing interconnections and/or creating entirely new interconnections.
Error Performance of Rectangular Pulse-shaped OTFS with Practical Receivers
In this letter, we investigate error performance of rectangular pulse-shaped orthogonal time frequency space (OTFS) modulation with a practical receiver.
Centralized and Decentralized Techniques for Analysis and Synthesis of Non-Linear Networked Systems
Second, we show that the centralized interconnection topology \emph{synthesis} techniques for these NSCs can also be developed as LMI problems.
Distributed Adaptive Backstepping Control for Vehicular Platoons with Mismatched Disturbances Using Vector String Lyapunov Functions
Using this notion, we propose an adaptive backstepping controller for the platoon such that the compositionality and the distributed nature of the controller can be ensured while the internal stability and string stability of the closed-loop system are formally guaranteed.
PSL is Dead. Long Live PSL
In this paper, we show that by merging machine learning techniques with PSL monitors, we can extend PSL to work on continuous domains.
A Decentralized Analysis and Control Synthesis Approach for Networked Systems with Arbitrary Interconnections
Subsequently, we also specialize all the derived results for discrete-time networked systems.
Mixed-Integer Programming for Signal Temporal Logic with Fewer Binary Variables
Signal Temporal Logic (STL) provides a convenient way of encoding complex control objectives for robotic and cyber-physical systems.
On-line Estimation of Stability and Passivity Metrics
We consider the problem of on-line evaluation of critical characteristic parameters such as the L_2-gain (L2G), input feedforward passivity index (IFP) and output feedback passivity index (OFP) of non-linear systems using their input-output data.
Robust Approximate Simulation for Hierarchical Control of Piecewise Affine Systems under Bounded Disturbances
First, a lower-dimensional linear system (abstraction) and an associated interface are designed to enable the output of the PWA system (concrete system) to track the output of the abstraction.
A More Scalable Mixed-Integer Encoding for Metric Temporal Logic
The state-of-the-art in optimal control from timed temporal logic specifications, including Metric Temporal Logic (MTL) and Signal Temporal Logic (STL), is based on Mixed-Integer Convex Programming (MICP).
idSTLPy: A Python Toolbox for Active Perception and Control
This paper describes a Python toolbox for active perception and control synthesis of probabilistic signal temporal logic (PrSTL) formulas of switched linear systems with additive Gaussian disturbances and measurement noises.
Active Perception and Control from PrSTL Specifications
This work combines symbolic control with active perception to achieve complex tasks in a partially observed and noisy control system with hybrid dynamics.
The Stackelberg Equilibrium for One-sided Zero-sum Partially Observable Stochastic Games
We propose a space partition approach to solve the game iteratively and show that the value function of the leader is piece-wise linear and the value function of the follower is piece-wise constant for multiple stages.
Backstepping Mean-Field Density Control for Large-Scale Heterogeneous Nonlinear Stochastic Systems
In this work, we present a backstepping design algorithm that extends density control to heterogeneous and higher-order stochastic systems in strict-feedback forms.
SPAN: Subgraph Prediction Attention Network for Dynamic Graphs
This paper proposes a novel model for predicting subgraphs in dynamic graphs, an extension of traditional link prediction.
Distributed Mean-Field Density Estimation for Large-Scale Systems
This work studies how to estimate the mean-field density of large-scale systems in a distributed manner.
Feedback Interconnected Mean-Field Density Estimation and Control
Specifically, we propose new density control laws which use the mean-field density and its gradient as feedback, and prove that they are globally input-to-state stable (ISS) with respect to estimation errors.
Field Estimation using Robotic Swarms through Bayesian Regression and Mean-Field Feedback
Recent years have seen an increased interest in using mean-field density based modelling and control strategy for deploying robotic swarms.
Distributed Density Filtering for Large-Scale Systems Using Mean-Filed Models
In this work, we further study how to decentralize the density filter such that each agent can estimate the global density only based on its local observation and communication with neighbors.
Specification mining and automated task planning for autonomous robots based on a graph-based spatial temporal logic
For knowledge representation, we use a graph-based spatial temporal logic (GSTL) to capture spatial and temporal information of related skills demonstrated by demo videos.
Transporting Robotic Swarms via Mean-Field Feedback Control
With the rapid development of AI and robotics, transporting a large swarm of networked robots has foreseeable applications in the near future.
Kalman Filtering with Gaussian Processes Measurement Noise
We propose general Gaussian Processes as a non-parametric model for correlated measurement noise that is flexible enough to accurately reflect correlation in time, yet simple enough to enable efficient computation.
A Co-analysis Framework for Exploring Multivariate Scientific Data
In this paper, we propose a co-analysis framework based on biclusters, which are two subsets of variables and voxels with close scalar-value relationships, to guide the process of visually exploring multivariate data.
Multivariate Spatial Data Visualization: A Survey
Multivariate spatial data plays an important role in computational science and engineering simulations.
Dynamic Network Embeddings for Network Evolution Analysis
Network embeddings learn to represent nodes as low-dimensional vectors to preserve the proximity between nodes and communities of the network for network analysis.
A Learning Based Optimal Human Robot Collaboration with Linear Temporal Logic Constraints
This paper considers an optimal task allocation problem for human robot collaboration in human robot systems with persistent tasks.
Supervisor Synthesis of POMDP based on Automata Learning
The learning algorithm is sound and complete.
