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Found 9 papers, 4 papers with code
From “Before” to “After”: Generating Natural Language Instructions from Image Pairs in a Simple Visual Domain
We find that it is, and investigate several simple baselines, taking these from the related task of image captioning.
Sharing the Cost of Success: A Game for Evaluating and Learning Collaborative Multi-Agent Instruction Giving and Following Policies
In collaborative goal-oriented settings, the participants are not only interested in achieving a successful outcome, but do also implicitly negotiate the effort they put into the interaction (by adapting to each other).
Learning Communication Policies for Different Follower Behaviors in a Collaborative Reference Game
Albrecht and Stone (2018) state that modeling of changing behaviors remains an open problem "due to the essentially unconstrained nature of what other agents may do".
Pento-DIARef: A Diagnostic Dataset for Learning the Incremental Algorithm for Referring Expression Generation from Examples
NLP tasks are typically defined extensionally through datasets containing example instantiations (e. g., pairs of image i and text t), but motivated intensionally through capabilities invoked in verbal descriptions of the task (e. g., "t is a description of i, for which the content of i needs to be recognised and understood").
Yes, this Way! Learning to Ground Referring Expressions into Actions with Intra-episodic Feedback from Supportive Teachers
The ability to pick up on language signals in an ongoing interaction is crucial for future machine learning models to collaborate and interact with humans naturally.
Clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents
Recent work has proposed a methodology for the systematic evaluation of "Situated Language Understanding Agents"-agents that operate in rich linguistic and non-linguistic contexts-through testing them in carefully constructed interactive settings.
Spatial Attention as an Interface for Image Captioning Models
The internal workings of modern deep learning models stay often unclear to an external observer, although spatial attention mechanisms are involved.
Can Neural Image Captioning be Controlled via Forced Attention?
Learned dynamic weighting of the conditioning signal (attention) has been shown to improve neural language generation in a variety of settings.
Detecting cities in aerial night-time images by learning structural invariants using single reference augmentation
First a principal component analysis in conjunction with a Fourier transform is trained on a single reference augmentation training dataset using the city images.
