Papers by Dongding Lin
Instruct Once, Chat Consistently in Multiple Rounds: An Efficient Tuning Framework for Dialogue (2024.acl-long)
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| Challenge: | Tuning language models for dialogue generation has been a prevalent paradigm for building capable dialogue agents. |
| Approach: | They propose a multi-round interactive dialogue tuning framework that models the speaker roles of agent and user separately. |
| Outcome: | The proposed framework performs superior to fine-tuning and improves dialogue consistency. |
Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation (2026.acl-long)
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| Challenge: | Situated conversational recommendation (SCR) uses visual scenes grounded in specific environments and natural language dialogue to deliver contextually appropriate recommendations. |
| Approach: | They propose a framework that integrates scene transition estimation and Bayesian inverse inference to provide contextually appropriate recommendations. |
| Outcome: | The proposed framework achieves superiority over baselines on two representative benchmarks on dynamic scene transitions and implicit user intents. |
Target-oriented Proactive Dialogue Systems with Personalization: Problem Formulation and Dataset Curation (2023.emnlp-main)
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| Challenge: | a recent study defines a conversation target from the system side to proactively steer conversations toward predefined targets or accomplish specific system-side goals. |
| Approach: | They propose a dataset curation framework that automatically curations a large-scale personalized dialogue dataset using a role-playing approach. |
| Outcome: | The proposed dataset is of high quality and could contribute to exploring personalized target-oriented dialogue. |
Dialogue Planning via Brownian Bridge Stochastic Process for Goal-directed Proactive Dialogue (2023.findings-acl)
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| Challenge: | Goal-directed dialogue systems aim to proactively reach a pre-determined target through multi-turn conversations. |
| Approach: | They propose a coherent dialogue planning approach that uses a stochastic process to model the temporal dynamics of dialogue paths. |
| Outcome: | The proposed approach generates more coherent utterances and achieves the goal with a higher success rate. |