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Found 9 papers, 6 papers with code
Knowledge Transfer between Structured and Unstructured Sources for Complex Question Answering
More fine-grained analyses on transfer behaviors reveal the types of transferred knowledge and transfer patterns.
A Multi-Aspect Framework for Counter Narrative Evaluation using Large Language Models
Counter narratives - informed responses to hate speech contexts designed to refute hateful claims and de-escalate encounters - have emerged as an effective hate speech intervention strategy.
A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents
There is a surprisingly large gap between the speed and scale of their development and deployment and our understanding of their safety risks.
Controllable Decontextualization of Yes/No Question and Answers into Factual Statements
Yes/No or polar questions represent one of the main linguistic question categories.
Roll Up Your Sleeves: Working with a Collaborative and Engaging Task-Oriented Dialogue System
We introduce TacoBot, a user-centered task-oriented digital assistant designed to guide users through complex real-world tasks with multiple steps.
MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing
To address this issue, we introduce MagicBrush (https://osu-nlp-group. github. io/MagicBrush/), the first large-scale, manually annotated dataset for instruction-guided real image editing that covers diverse scenarios: single-turn, multi-turn, mask-provided, and mask-free editing.
Bootstrapping a User-Centered Task-Oriented Dialogue System
We present TacoBot, a task-oriented dialogue system built for the inaugural Alexa Prize TaskBot Challenge, which assists users in completing multi-step cooking and home improvement tasks.
Towards Transparent Interactive Semantic Parsing via Step-by-Step Correction
In this work, we investigate an interactive semantic parsing framework that explains the predicted logical form step by step in natural language and enables the user to make corrections through natural-language feedback for individual steps.
