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Found 14 papers, 5 papers with code
Dyna-bAbI: unlocking bAbI’s potential with dynamic synthetic benchmarking
However, the main synthetic resource for story understanding, the bAbI benchmark, lacks such a systematic mechanism for controllable task generation.
"What's my model inside of?": Exploring the role of environments for grounded natural language understanding
In contrast to classical cognitive science which studied brains in isolation, ecological approaches focused on the role of the body and environment in shaping cognition.
Natural Language Understanding
Procedural Text Understanding
Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs
Can we teach natural language understanding models to track their beliefs through intermediate points in text?
Dyna-bAbI: unlocking bAbI's potential with dynamic synthetic benchmarking
However, the main synthetic resource for story understanding, the bAbI benchmark, lacks such a systematic mechanism for controllable task generation.
Scaling Creative Inspiration with Fine-Grained Functional Aspects of Ideas
Large repositories of products, patents and scientific papers offer an opportunity for building systems that scour millions of ideas and help users discover inspirations.
Process-Level Representation of Scientific Protocols with Interactive Annotation
We develop Process Execution Graphs (PEG), a document-level representation of real-world wet lab biochemistry protocols, addressing challenges such as cross-sentence relations, long-range coreference, grounding, and implicit arguments.
Language (Re)modelling: Towards Embodied Language Understanding
While natural language understanding (NLU) is advancing rapidly, today's technology differs from human-like language understanding in fundamental ways, notably in its inferior efficiency, interpretability, and generalization.
Ecological Semantics: Programming Environments for Situated Language Understanding
Large-scale natural language understanding (NLU) systems have made impressive progress: they can be applied flexibly across a variety of tasks, and employ minimal structural assumptions.
Y'all should read this! Identifying Plurality in Second-Person Personal Pronouns in English Texts
Distinguishing between singular and plural {``}you{''} in English is a challenging task which has potential for downstream applications, such as machine translation or coreference resolution.
Yall should read this! Identifying Plurality in Second-Person Personal Pronouns in English Texts
Distinguishing between singular and plural "you" in English is a challenging task which has potential for downstream applications, such as machine translation or coreference resolution.
Playing by the Book: An Interactive Game Approach for Action Graph Extraction from Text
Understanding procedural text requires tracking entities, actions and effects as the narrative unfolds.
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions
Expressive efficiency refers to the ability of a network architecture to realize functions that require an alternative architecture to be much larger.
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions
By introducing and analyzing the concept of mixed tensor decompositions, we prove that interconnecting dilated convolutional networks can lead to expressive efficiency.
Tensorial Mixture Models
Other methods, based on arithmetic circuits and sum-product networks, do allow tractable marginalization, but their performance is challenged by the need to learn the structure of a circuit.
