activity
20172022
most citedNLVR2 Visual Bias Analysis

8 citations · 11 across the 5 of their papers we have counts for

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Showing cs.CLShow all

8 papers · 1 filter

cs.CL2022

Abstract Visual Reasoning with Tangram Shapes

Anya Ji, Noriyuki Kojima, Noah Rush +4

We introduce KiloGram, a resource for studying abstract visual reasoning in humans and machines. Drawing on the history of tangram puzzles as stimuli in cognitive science, we build…

cs.CL2021

Analysis of Language Change in Collaborative Instruction Following

Anna Effenberger, Eva Yan, Rhia Singh +2

We analyze language change over time in a collaborative, goal-oriented instructional task, where utility-maximizing participants form conventions and increase their expertise. Prio…

cs.CL20212 cited

Continual Learning for Grounded Instruction Generation by Observing Human Following Behavior

Noriyuki Kojima, Alane Suhr, Yoav Artzi

We study continual learning for natural language instruction generation, by observing human users' instruction execution. We focus on a collaborative scenario, where the system bot…

cs.CL20198 cited

NLVR2 Visual Bias Analysis

Alane Suhr, Yoav Artzi

NLVR2 (Suhr et al., 2019) was designed to be robust for language bias through a data collection process that resulted in each natural language sentence appearing with both true and…

cs.CL2018

A Corpus for Reasoning About Natural Language Grounded in Photographs

Alane Suhr, Stephanie Zhou, Ally Zhang +3

We introduce a new dataset for joint reasoning about natural language and images, with a focus on semantic diversity, compositionality, and visual reasoning challenges. The data co…

cs.CL2018

Situated Mapping of Sequential Instructions to Actions with Single-step Reward Observation

Alane Suhr, Yoav Artzi

We propose a learning approach for mapping context-dependent sequential instructions to actions. We address the problem of discourse and state dependencies with an attention-based…