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A Large-Scale Dataset for Empathetic Response Generation

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Graph Chatbot

Publications associées (5)

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Solving the Cold-Start Problem for the Edge: Clustering and Adaptive Deep Learning for Emotion Detection

José Angel Miranda Calero

Designing AI-based applications personalized to each user's behavior presents significant challenges due to the cold start problem and the impracticality of extensive individual data labeling. These challenges are further compounded when deploying such app ...

IEEE2025

Depth-optimal Buffer and Splitter Insertion and Optimization in AQFP Circuits

Giovanni De Micheli, Alessandro Tempia Calvino

The Adiabatic Quantum-Flux Parametron (AQFP) is an energy-efficient superconducting logic family. AQFP technology requires buffer and splitting elements (B/S) to be inserted to satisfy path-balancing and fanout-branching constraints. B/S insertion policies ...

IEEE2023

A Taxonomy of Empathetic Questions in Social Dialogs

Pearl Pu Faltings, Kalpani Anuradha Welivita, Ekaterina Svikhnushina

Effective question-asking is a crucial component of a successful conversational chatbot. It could help the bots manifest empathy and render the interaction more engaging by demonstrating attention to the speaker's emotions. However, current dialog generati ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2022

Optimizing Adiabatic Quantum-Flux-Parametron (AQFP) Circuits using an Exact Database

Giovanni De Micheli, Dewmini Sudara Marakkalage

Adiabatic Quantum-Flux-Parametron (AQFP) is a family of superconducting electronic (SCE) circuits exhibiting high energy efficiency. In AQFP technology, logic gates require splitters to drive multiple fanouts and both the logic gates and the splitters are ...

IEEE2021

Parallelizing Maximal Clique Enumeration on Modern Manycore Processors

Paolo Ienne, Jovan Blanusa

Many fundamental graph mining problems, such as maximal clique enumeration and subgraph isomorphism, can be solved using combinatorial algorithms that are naturally expressed in a recursive form. However, recursive graph mining algorithms suffer from a hig ...

IEEE COMPUTER SOC2020