26 citations · 42 across the 8 of their papers we have counts for
11 papers
NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks
Chia-Yu Hung, Qi Sun, Pengfei Hong +5
Existing Visual-Language-Action (VLA) models have shown promising performance in zero-shot scenarios, demonstrating impressive task execution and reasoning capabilities. However, a…
Emma-X: An Embodied Multimodal Action Model with Grounded Chain of Thought and Look-ahead Spatial Reasoning
Qi Sun, Pengfei Hong, Tej Deep Pala +4
Traditional reinforcement learning-based robotic control methods are often task-specific and fail to generalize across diverse environments or unseen objects and instructions. Visu…
Evaluating LLMs' Mathematical and Coding Competency through Ontology-guided Interventions
Pengfei Hong, Navonil Majumder, Deepanway Ghosal +3
Recent advancements in Large Language Models (LLMs) have showcased striking results on existing logical reasoning benchmarks, with some models even surpassing human performance. Ho…
INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language Models
Yew Ken Chia, Pengfei Hong, Lidong Bing +1
Instruction-tuned large language models have revolutionized natural language processing and have shown great potential in applications such as conversational agents. These models,…
Uncertainty Guided Label Denoising for Document-level Distant Relation Extraction
Qi Sun, Kun Huang, Xiaocui Yang +3
Document-level relation extraction (DocRE) aims to infer complex semantic relations among entities in a document. Distant supervision (DS) is able to generate massive auto-labeled…
Few-shot Joint Multimodal Aspect-Sentiment Analysis Based on Generative Multimodal Prompt
Xiaocui Yang, Shi Feng, Daling Wang +5
We have witnessed the rapid proliferation of multimodal data on numerous social media platforms. Conventional studies typically require massive labeled data to train models for Mul…
ReMask: A Robust Information-Masking Approach for Domain Counterfactual Generation
Pengfei Hong, Rishabh Bhardwaj, Navonil Majumdar +2
Domain shift is a big challenge in NLP, thus, many approaches resort to learning domain-invariant features to mitigate the inference phase domain shift. Such methods, however, fail…
CIDER: Commonsense Inference for Dialogue Explanation and Reasoning
Deepanway Ghosal, Pengfei Hong, Siqi Shen +3
Commonsense inference to understand and explain human language is a fundamental research problem in natural language processing. Explaining human conversations poses a great challe…
Recognizing Emotion Cause in Conversations
Soujanya Poria, Navonil Majumder, Devamanyu Hazarika +9
We address the problem of recognizing emotion cause in conversations, define two novel sub-tasks of this problem, and provide a corresponding dialogue-level dataset, along with str…
MIME: MIMicking Emotions for Empathetic Response Generation
Navonil Majumder, Pengfei Hong, Shanshan Peng +5
Current approaches to empathetic response generation view the set of emotions expressed in the input text as a flat structure, where all the emotions are treated uniformly. We argu…
Dialogue Relation Extraction with Document-level Heterogeneous Graph Attention Networks
Hui Chen, Pengfei Hong, Wei Han +2
Dialogue relation extraction (DRE) aims to detect the relation between two entities mentioned in a multi-party dialogue. It plays an important role in constructing knowledge graphs…