Angeliki Lazaridou | DeepAI

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∙ 07/11/2023

Towards Robust and Efficient Continual Language Learning

As the application space of language models continues to evolve, a natur...

0 Adam Fisch, et al. ∙

∙ 05/23/2022

StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering Models

Knowledge and language understanding of models evaluated through questio...

0 Adam Liska, et al. ∙

∙ 03/10/2022

Internet-augmented language models through few-shot prompting for open-domain question answering

In this work, we aim to capitalize on the unique few-shot capabilities o...

0 Angeliki Lazaridou, et al. ∙

∙ 02/03/2021

Pitfalls of Static Language Modelling

Our world is open-ended, non-stationary and constantly evolving; thus wh...

0 Angeliki Lazaridou, et al. ∙

∙ 01/25/2021

Emergent Communication under Competition

The literature in modern machine learning has only negative results for ...

0 Michael Noukhovitch, et al. ∙

∙ 10/20/2020

Negotiating Team Formation Using Deep Reinforcement Learning

When autonomous agents interact in the same environment, they must often...

0 Yoram Bachrach, et al. ∙

∙ 06/03/2020

Emergent Multi-Agent Communication in the Deep Learning Era

The ability to cooperate through language is a defining feature of human...

12 Angeliki Lazaridou, et al. ∙

∙ 05/14/2020

Multi-agent Communication meets Natural Language: Synergies between Functional and Structural Language Learning

We present a method for combining multi-agent communication and traditio...

2 Angeliki Lazaridou, et al. ∙

∙ 04/21/2020

Experience Grounds Language

Successful linguistic communication relies on a shared experience of the...

1 Yonatan Bisk, et al. ∙

∙ 12/12/2019

Shaping representations through communication: community size effect in artificial learning systems

Motivated by theories of language and communication that explain why com...

6 Olivier Tieleman, et al. ∙

∙ 12/11/2019

Biases for Emergent Communication in Multi-agent Reinforcement Learning

We study the problem of emergent communication, in which language arises...

0 Tom Eccles, et al. ∙

∙ 01/31/2019

Learning and Evaluating General Linguistic Intelligence

We define general linguistic intelligence as the ability to reuse previo...

8 Dani Yogatama, et al. ∙

∙ 10/19/2018

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning

We propose a unified mechanism for achieving coordination and communicat...

0 Natasha Jaques, et al. ∙

∙ 10/19/2018

Intrinsic Social Motivation via Causal Influence in Multi-Agent RL

We derive a new intrinsic social motivation for multi-agent reinforcemen...

0 Natasha Jaques, et al. ∙

∙ 04/11/2018

Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input

The ability of algorithms to evolve or learn (compositional) communicati...

0 Angeliki Lazaridou, et al. ∙

∙ 04/11/2018

Emergent Communication through Negotiation

Multi-agent reinforcement learning offers a way to study how communicati...

0 Kris Cao, et al. ∙

∙ 04/06/2018

Compositional Obverter Communication Learning From Raw Visual Input

One of the distinguishing aspects of human language is its compositional...

0 Edward Choi, et al. ∙

∙ 11/02/2017

A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning

To achieve general intelligence, agents must learn how to interact with ...

0 Marc Lanctot, et al. ∙

∙ 07/25/2017

The RepEval 2017 Shared Task: Multi-Genre Natural Language Inference with Sentence Representations

This paper presents the results of the RepEval 2017 Shared Task, which e...

0 Nikita Nangia, et al. ∙

∙ 01/31/2017

CommAI: Evaluating the first steps towards a useful general AI

With machine learning successfully applied to new daunting problems almo...

0 Marco Baroni, et al. ∙

∙ 12/21/2016

Multi-Agent Cooperation and the Emergence of (Natural) Language

The current mainstream approach to train natural language systems is to ...

0 Angeliki Lazaridou, et al. ∙

∙ 06/20/2016

The LAMBADA dataset: Word prediction requiring a broad discourse context

We introduce LAMBADA, a dataset to evaluate the capabilities of computat...

0 Denis Paperno, et al. ∙

∙ 05/23/2016

Towards Multi-Agent Communication-Based Language Learning

We propose an interactive multimodal framework for language learning. In...

0 Angeliki Lazaridou, et al. ∙

∙ 03/08/2016

The red one!: On learning to refer to things based on their discriminative properties

As a first step towards agents learning to communicate about their visua...

0 Angeliki Lazaridou, et al. ∙

∙ 06/10/2015

Unveiling the Dreams of Word Embeddings: Towards Language-Driven Image Generation

We introduce language-driven image generation, the task of generating an...

0 Angeliki Lazaridou, et al. ∙

∙ 01/12/2015

From Visual Attributes to Adjectives through Decompositional Distributional Semantics

As automated image analysis progresses, there is increasing interest in ...

0 Angeliki Lazaridou, et al. ∙

∙ 01/12/2015

Combining Language and Vision with a Multimodal Skip-gram Model

We extend the SKIP-GRAM model of Mikolov et al. (2013a) by taking visual...

0 Angeliki Lazaridou, et al. ∙

∙ 12/20/2014

Improving zero-shot learning by mitigating the hubness problem

The zero-shot paradigm exploits vector-based word representations extrac...

0 Georgiana Dinu, et al. ∙

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