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Found 11 papers, 0 papers with code
Generation and Extraction Combined Dialogue State Tracking with Hierarchical Ontology Integration
Recently, the focus of dialogue state tracking has expanded from single domain to multiple domains.
Conversational Crowdsensing: A Parallel Intelligence Powered Novel Sensing Approach
The transition from CPS-based Industry 4. 0 to CPSS-based Industry 5. 0 brings new requirements and opportunities to current sensing approaches, especially in light of recent progress in Chatbots and Large Language Models (LLMs).
The Risk of Federated Learning to Skew Fine-Tuning Features and Underperform Out-of-Distribution Robustness
To tackle the scarcity and privacy issues associated with domain-specific datasets, the integration of federated learning in conjunction with fine-tuning has emerged as a practical solution.
DAP: Domain-aware Prompt Learning for Vision-and-Language Navigation
Then we introduce soft visual prompts in the input space of the visual encoder in a pretrained model.
Asymmetrically Decentralized Federated Learning
To further improve algorithm performance and alleviate local heterogeneous overfitting in Federated Learning (FL), our algorithm combines the Sharpness Aware Minimization (SAM) optimizer and local momentum.
Prompt-based Context- and Domain-aware Pretraining for Vision and Language Navigation
In the indoor-aware stage, we apply an efficient tuning paradigm to learn deep visual prompts from an indoor dataset, in order to augment pretrained models with inductive biases towards indoor environments.
DFedADMM: Dual Constraints Controlled Model Inconsistency for Decentralized Federated Learning
To address the communication burden issues associated with federated learning (FL), decentralized federated learning (DFL) discards the central server and establishes a decentralized communication network, where each client communicates only with neighboring clients.
FedHiSyn: A Hierarchical Synchronous Federated Learning Framework for Resource and Data Heterogeneity
As the efficiency of training in the ring topology prefers devices with homogeneous resources, the classification based on the computing capacity mitigates the impact of straggler effects.
How to Evaluate Your Dialogue Models: A Review of Approaches
Evaluating the quality of a dialogue system is an understudied problem.
Question-Aware Memory Network for Multi-hop Question Answering in Human-Robot Interaction
We evaluate QA2MN on PathQuestion and WorldCup2014, two representative datasets for complex multi-hop question answering.
Combining Subgoal Graphs with Reinforcement Learning to Build a Rational Pathfinder
The first advantage of the proposed method is that SSG can solve the limitations of sparse reward and local minima trap for RL agents; thus, LSPI can be used to generate paths in complex environments.
