Search Results for author: Dongding Lin

Found 6 papers, 4 papers with code

Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive Dialogue

1 code implementation10 Mar 2024 Jian Wang, Dongding Lin, Wenjie Li

Inspired by decision-making theories in cognitive science, we propose a novel target-constrained bidirectional planning (TRIP) approach, which plans an appropriate dialogue path by looking ahead and looking back.

Dialogue Generation

Instruct Once, Chat Consistently in Multiple Rounds: An Efficient Tuning Framework for Dialogue

no code implementations10 Feb 2024 Jian Wang, Chak Tou Leong, Jiashuo Wang, Dongding Lin, Wenjie Li, Xiao-Yong Wei

Tuning pretrained language models for dialogue generation has been a prevalent paradigm for building capable dialogue agents.

Dialogue Generation

Target-oriented Proactive Dialogue Systems with Personalization: Problem Formulation and Dataset Curation

1 code implementation11 Oct 2023 Jian Wang, Yi Cheng, Dongding Lin, Chak Tou Leong, Wenjie Li

Target-oriented dialogue systems, designed to proactively steer conversations toward predefined targets or accomplish specific system-side goals, are an exciting area in conversational AI.

Dialogue Planning via Brownian Bridge Stochastic Process for Goal-directed Proactive Dialogue

1 code implementation9 May 2023 Jian Wang, Dongding Lin, Wenjie Li

The key to achieving this task lies in planning dialogue paths that smoothly and coherently direct conversations towards the target.

Dialogue Generation

COLA: Improving Conversational Recommender Systems by Collaborative Augmentation

no code implementations15 Dec 2022 Dongding Lin, Jian Wang, Wenjie Li

Inspired by collaborative filtering, we propose a collaborative augmentation (COLA) method to simultaneously improve both item representation learning and user preference modeling to address these issues.

CoLA Collaborative Filtering +2

Follow Me: Conversation Planning for Target-driven Recommendation Dialogue Systems

1 code implementation6 Aug 2022 Jian Wang, Dongding Lin, Wenjie Li

Recommendation dialogue systems aim to build social bonds with users and provide high-quality recommendations.

Dialogue Generation

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