21 citations · 56 across the 13 of their papers we have counts for
13 papers
"What's my model inside of?": Exploring the role of environments for grounded natural language understanding
Ronen Tamari
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. Similarly,…
Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs
Kyle Richardson, Ronen Tamari, Oren Sultan +3
Can we teach natural language understanding models to track their beliefs through intermediate points in text? We propose a representation learning framework called breakpoint mode…
From Users to (Sense)Makers: On the Pivotal Role of Stigmergic Social Annotation in the Quest for Collective Sensemaking
Ronen Tamari, Daniel Friedman, William Fischer +2
The web has become a dominant epistemic environment, influencing people's beliefs at a global scale. However, online epistemic environments are increasingly polluted, impairing soc…
Dyna-bAbI: unlocking bAbI's potential with dynamic synthetic benchmarking
Ronen Tamari, Kyle Richardson, Aviad Sar-Shalom +4
While neural language models often perform surprisingly well on natural language understanding (NLU) tasks, their strengths and limitations remain poorly understood. Controlled syn…
Scaling Creative Inspiration with Fine-Grained Functional Aspects of Ideas
Tom Hope, Ronen Tamari, Hyeonsu Kang +4
Large repositories of products, patents and scientific papers offer an opportunity for building systems that scour millions of ideas and help users discover inspirations. However,…
Process-Level Representation of Scientific Protocols with Interactive Annotation
Ronen Tamari, Fan Bai, Alan Ritter +1
We develop Process Execution Graphs (PEG), a document-level representation of real-world wet lab biochemistry protocols, addressing challenges such as cross-sentence relations, lon…
Language (Re)modelling: Towards Embodied Language Understanding
Ronen Tamari, Chen Shani, Tom Hope +3
While natural language understanding (NLU) is advancing rapidly, today's technology differs from human-like language understanding in fundamental ways, notably in its inferior effi…
Ecological Semantics: Programming Environments for Situated Language Understanding
Ronen Tamari, Gabriel Stanovsky, Dafna Shahaf +1
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 assump…
Yall should read this! Identifying Plurality in Second-Person Personal Pronouns in English Texts
Gabriel Stanovsky, Ronen Tamari
Distinguishing between singular and plural "you" in English is a challenging task which has potential for downstream applications, such as machine translation or coreference resolu…
Playing by the Book: An Interactive Game Approach for Action Graph Extraction from Text
Ronen Tamari, Hiroyuki Shindo, Dafna Shahaf +1
Understanding procedural text requires tracking entities, actions and effects as the narrative unfolds. We focus on the challenging real-world problem of action-graph extraction fr…
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions
Nadav Cohen, Or Sharir, Yoav Levine +3
The driving force behind convolutional networks - the most successful deep learning architecture to date, is their expressive power. Despite its wide acceptance and vast empirical…
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions
Nadav Cohen, Ronen Tamari, Amnon Shashua
The driving force behind deep networks is their ability to compactly represent rich classes of functions. The primary notion for formally reasoning about this phenomenon is express…
Tensorial Mixture Models
Or Sharir, Ronen Tamari, Nadav Cohen +1
Casting neural networks in generative frameworks is a highly sought-after endeavor these days. Contemporary methods, such as Generative Adversarial Networks, capture some of the ge…