21 citations · 67 across the 13 of their papers we have counts for
13 papers
PolyAlign: Conditional Human-Distribution Alignment
L. D. M. S. Sai Teja, Ufaq Khan, Sathira Silva +2
Post-training methods such as supervised fine-tuning (SFT) and preference optimization typically align language models toward a single global assistant behavior. While effective fo…
Bridging Scale Discrepancies in Robotic Control via Language-Based Action Representations
Yuchi Zhang, Churui Sun, Shiqi Liang +4
Recent end-to-end robotic manipulation research increasingly adopts architectures inspired by large language models to enable robust manipulation. However, a critical challenge ari…
Unstructured Text Enhanced Open-domain Dialogue System: A Systematic Survey
Longxuan Ma, Mingda Li, Weinan Zhang +2
Incorporating external knowledge into dialogue generation has been proven to benefit the performance of an open-domain Dialogue System (DS), such as generating informative or styli…
A Static and Dynamic Attention Framework for Multi Turn Dialogue Generation
Wei-Nan Zhang, Yiming Cui, Kaiyan Zhang +4
Recently, research on open domain dialogue systems have attracted extensive interests of academic and industrial researchers. The goal of an open domain dialogue system is to imita…
Visualizing attention zones in machine reading comprehension models
Yiming Cui, Wei-Nan Zhang, Ting Liu
The attention mechanism plays an important role in the machine reading comprehension (MRC) model. Here, we describe a pipeline for building an MRC model with a pretrained language…
A Stack-Propagation Framework for Low-Resource Personalized Dialogue Generation
Haoyu Song, Wei-Nan Zhang, Kaiyan Zhang +1
With the resurgent interest in building open-domain dialogue systems, the dialogue generation task has attracted increasing attention over the past few years. This task is usually…
Policy-driven Knowledge Selection and Response Generation for Document-grounded Dialogue
Longxuan Ma, Jiapeng Li, Mingda Li +2
Document-grounded dialogue (DGD) uses documents as external knowledge for dialogue generation. Correctly understanding the dialogue context is crucial for selecting knowledge from…
Harnessing the Power of Large Language Models for Empathetic Response Generation: Empirical Investigations and Improvements
Yushan Qian, Wei-Nan Zhang, Ting Liu
Empathetic dialogue is an indispensable part of building harmonious social relationships and contributes to the development of a helpful AI. Previous approaches are mainly based on…
Through the Lens of Core Competency: Survey on Evaluation of Large Language Models
Ziyu Zhuang, Qiguang Chen, Longxuan Ma +7
From pre-trained language model (PLM) to large language model (LLM), the field of natural language processing (NLP) has witnessed steep performance gains and wide practical uses. T…
I run as fast as a rabbit, can you? A Multilingual Simile Dialogue Dataset
Longxuan Ma, Weinan Zhang, Shuhan Zhou +3
A simile is a figure of speech that compares two different things (called the tenor and the vehicle) via shared properties. The tenor and the vehicle are usually connected with com…
SelF-Eval: Self-supervised Fine-grained Dialogue Evaluation
Longxuan Ma, Ziyu Zhuang, Weinan Zhang +2
This paper introduces a novel Self-supervised Fine-grained Dialogue Evaluation framework (SelF-Eval). The core idea is to model the correlation between turn quality and the entire…
CLIP Models are Few-shot Learners: Empirical Studies on VQA and Visual Entailment
Haoyu Song, Li Dong, Wei-Nan Zhang +2
CLIP has shown a remarkable zero-shot capability on a wide range of vision tasks. Previously, CLIP is only regarded as a powerful visual encoder. However, after being pre-trained b…
Multilingual Multi-Aspect Explainability Analyses on Machine Reading Comprehension Models
Yiming Cui, Wei-Nan Zhang, Wanxiang Che +3
Achieving human-level performance on some of the Machine Reading Comprehension (MRC) datasets is no longer challenging with the help of powerful Pre-trained Language Models (PLMs).…