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Found 11 papers, 11 papers with code
CommVQA: Situating Visual Question Answering in Communicative Contexts
Current visual question answering (VQA) models tend to be trained and evaluated on image-question pairs in isolation.
ContextRef: Evaluating Referenceless Metrics For Image Description Generation
None of the methods is successful with ContextRef, but we show that careful fine-tuning yields substantial improvements.
Context-VQA: Towards Context-Aware and Purposeful Visual Question Answering
We also find that context effects are especially important when participants can't see the image.
Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics
Few images on the Web receive alt-text descriptions that would make them accessible to blind and low vision (BLV) users.
Color Overmodification Emerges from Data-Driven Learning and Pragmatic Reasoning
It seems likely that these patterns are shaped by the environment a speaker is exposed to in complex ways.
Causal Distillation for Language Models
Distillation efforts have led to language models that are more compact and efficient without serious drops in performance.
Inducing Causal Structure for Interpretable Neural Networks
In IIT, we (1) align variables in a causal model (e. g., a deterministic program or Bayesian network) with representations in a neural model and (2) train the neural model to match the counterfactual behavior of the causal model on a base input when aligned representations in both models are set to be the value they would be for a source input.
ReaSCAN: Compositional Reasoning in Language Grounding
The ability to compositionally map language to referents, relations, and actions is an essential component of language understanding.
Concadia: Towards Image-Based Text Generation with a Purpose
Current deep learning models often achieve excellent results on benchmark image-to-text datasets but fail to generate texts that are useful in practice.
Modeling Subjective Assessments of Guilt in Newspaper Crime Narratives
Crime reporting is a prevalent form of journalism with the power to shape public perceptions and social policies.
When redundancy is useful: A Bayesian approach to 'overinformative' referring expressions
Crucially, we relax the assumption that informativeness is computed with respect to a deterministic Boolean semantics, in favor of a non-deterministic continuous semantics.
