40 citations · 107 across the 11 of their papers we have counts for
11 papers
Residual Stream Analysis of Overfitting And Structural Disruptions
Quan Liu, Han Zhou, Wenquan Wu +2
Ensuring that large language models (LLMs) remain both helpful and harmless poses a significant challenge: fine-tuning on repetitive safety datasets, where unsafe prompts are paire…
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…
PLATO-K: Internal and External Knowledge Enhanced Dialogue Generation
Siqi Bao, Huang He, Jun Xu +7
Recently, the practical deployment of open-domain dialogue systems has been plagued by the knowledge issue of information deficiency and factual inaccuracy. To this end, we introdu…
CDConv: A Benchmark for Contradiction Detection in Chinese Conversations
Chujie Zheng, Jinfeng Zhou, Yinhe Zheng +6
Dialogue contradiction is a critical issue in open-domain dialogue systems. The contextualization nature of conversations makes dialogue contradiction detection rather challenging.…
Link the World: Improving Open-domain Conversation with Dynamic Spatiotemporal-aware Knowledge
Han Zhou, Xinchao Xu, Wenquan Wu +5
Making chatbots world aware in a conversation like a human is a crucial challenge, where the world may contain dynamic knowledge and spatiotemporal state. Several recent advances h…
Towards Multi-Turn Empathetic Dialogs with Positive Emotion Elicitation
Shihang Wang, Xinchao Xu, Wenquan Wu +3
Emotional support is a crucial skill for many real-world scenarios, including caring for the elderly, mental health support, and customer service chats. This paper presents a novel…
Long Time No See! Open-Domain Conversation with Long-Term Persona Memory
Xinchao Xu, Zhibin Gou, Wenquan Wu +4
Most of the open-domain dialogue models tend to perform poorly in the setting of long-term human-bot conversations. The possible reason is that they lack the capability of understa…
PLATO-XL: Exploring the Large-scale Pre-training of Dialogue Generation
Siqi Bao, Huang He, Fan Wang +11
To explore the limit of dialogue generation pre-training, we present the models of PLATO-XL with up to 11 billion parameters, trained on both Chinese and English social media conve…
A Unified Pre-training Framework for Conversational AI
Siqi Bao, Bingjin Chen, Huang He +7
In this work, we explore the application of PLATO-2 on various dialogue systems, including open-domain conversation, knowledge grounded dialogue, and task-oriented conversation. PL…
PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning
Siqi Bao, Huang He, Fan Wang +6
To build a high-quality open-domain chatbot, we introduce the effective training process of PLATO-2 via curriculum learning. There are two stages involved in the learning process.…
Proactive Human-Machine Conversation with Explicit Conversation Goals
Wenquan Wu, Zhen Guo, Xiangyang Zhou +4
Though great progress has been made for human-machine conversation, current dialogue system is still in its infancy: it usually converses passively and utters words more as a matte…