80 citations · 471 across the 61 of their papers we have counts for
6 papers · 1 filter
AUGUST: an Automatic Generation Understudy for Synthesizing Conversational Recommendation Datasets
Yu Lu, Junwei Bao, Zichen Ma +4
High-quality data is essential for conversational recommendation systems and serves as the cornerstone of the network architecture development and training strategy design. Existin…
Heterogeneous Value Alignment Evaluation for Large Language Models
Zhaowei Zhang, Ceyao Zhang, Nian Liu +5
The emergent capabilities of Large Language Models (LLMs) have made it crucial to align their values with those of humans. However, current methodologies typically attempt to assig…
MoNET: Tackle State Momentum via Noise-Enhanced Training for Dialogue State Tracking
Haoning Zhang, Junwei Bao, Haipeng Sun +4
Dialogue state tracking (DST) aims to convert the dialogue history into dialogue states which consist of slot-value pairs. As condensed structural information memorizing all histor…
CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Tracking
Haoning Zhang, Junwei Bao, Haipeng Sun +3
Few-shot dialogue state tracking (DST) is a realistic problem that trains the DST model with limited labeled data. Existing few-shot methods mainly transfer knowledge learned from…
Composable Text Controls in Latent Space with ODEs
Guangyi Liu, Zeyu Feng, Yuan Gao +7
Real-world text applications often involve composing a wide range of text control operations, such as editing the text w.r.t. an attribute, manipulating keywords and structure, and…
Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation
Guangyi Liu, Zichao Yang, Tianhua Tao +6
Neural text generation models are typically trained by maximizing log-likelihood with the sequence cross entropy (CE) loss, which encourages an exact token-by-token match between a…