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Found 15 papers, 7 papers with code
Decoupling Strategy and Generation in Negotiation Dialogues
We consider negotiation settings in which two agents use natural language to bargain on goods.
SocialIQA: Commonsense Reasoning about Social Interactions
We introduce Social IQa, the first largescale benchmark for commonsense reasoning about social situations.
Ranked #9 on
Question Answering
on SIQA
Social IQa: Commonsense Reasoning about Social Interactions
We introduce Social IQa, the first large-scale benchmark for commonsense reasoning about social situations.
Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task-Oriented Dialogue Systems
Existing goal-oriented dialogue datasets focus mainly on identifying slots and values.
GOLD: Improving Out-of-Scope Detection in Dialogues using Data Augmentation
Practical dialogue systems require robust methods of detecting out-of-scope (OOS) utterances to avoid conversational breakdowns and related failure modes.
Clean or Annotate: How to Spend a Limited Data Collection Budget
Crowdsourcing platforms are often used to collect datasets for training machine learning models, despite higher levels of inaccurate labeling compared to expert labeling.
DG2: Data Augmentation Through Document Grounded Dialogue Generation
Collecting data for training dialog systems can be extremely expensive due to the involvement of human participants and need for extensive annotation.
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.
Data Augmentation for Intent Classification
Training accurate intent classifiers requires labeled data, which can be costly to obtain.
Sources of Noise in Dialogue and How to Deal with Them
Training dialogue systems often entails dealing with noisy training examples and unexpected user inputs.
Stabilized In-Context Learning with Pre-trained Language Models for Few Shot Dialogue State Tracking
Prompt-based methods with large pre-trained language models (PLMs) have shown impressive unaided performance across many NLP tasks.
Mixture of Soft Prompts for Controllable Data Generation
Large language models (LLMs) effectively generate fluent text when the target output follows natural language patterns.
GPT-4 Technical Report
We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs.
Ranked #1 on
Long-Context Understanding
on Ada-LEval (BestAnswer)
Using Textual Interface to Align External Knowledge for End-to-End Task-Oriented Dialogue Systems
We demonstrate our paradigm in practice through MultiWOZ-Remake, including an interactive textual interface built for the MultiWOZ database and a correspondingly re-processed dataset.
Symbolic Planning and Code Generation for Grounded Dialogue
Large language models (LLMs) excel at processing and generating both text and code.
