Towards Understanding Situated Natural Language

By Antoine Bordes, Nicolas Usunier, Ronan Collobert, Jason Aaron Edward Weston. 2010

31 citations recorded by the source corpus.

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In Natural Language Processing

Citations in the corpus

Memory Networks (2014, methodology): “Similar to the approach of [2] we also built a simple simulation of 4 characters, 4 objects and 4 rooms – with characters moving around, picking up and dropping objects.”
Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks (2015, background): “Our simulation follows those of (Bordes et al., 2010; Weston et al., 2014) but is somewhat more complex.”
A semantic matching energy function for learning with multi-relational data (2013, background): “A relation is denoted by a triplet ( lhs , rel , rhs ), where lhs is the left entity, rhs the right one and rel the type of relation between them.”
Learning Structured Embeddings of Knowledge Bases (2011, methodology): “…in the Freebase set are ( marylin monroe, profession, actress), ( pablo picasso, place of birth, m` alaga) or ( john f kennedy, religion, catholicism), and in the WordNet set: ( door 1, has part, lock 2), ( brain 1, type of, neural structure 1) Table 2: Relation types of KBs used in this paper.”
Learning to Speak and Act in a Fantasy Text Adventure Game (2019, background): “Yang et al. (2017) and Bordes et al. (2010) proposed small world setups for instruction following or labeling, but these are much more restricted than the large multi-player text adventure game environment with rich dialogue that we propose here.”
Mastering the Dungeon: Grounded Language Learning by Mechanical Turker Descent (2017, neutral): “. Grounding language in an interactive environment is an active area of research, however a number of recent works employ synthetic, templated language only (Sukhbaatar et al., 2015; Yu et al., 2017; Bordes et al., 2010; Hermann et al., 2017; Mikolov et al., 2015; Chaplot et al., 2017). Some works t”
Toward Automated Quest Generation in Text-Adventure Games (2019, background): “Although there has been much work recently on text-adventure gameplay (Bordes et al., 2010; He et al., 2016; Narasimhan et al., 2015; Fulda et al., 2017; Yang et al., 2018; Haroush et al., 2018; Cˆot´e et al., 2018; Tao et al., 2018; Ammanabrolu and Riedl, 2019a; Hausknecht et al., 2019a;…”
Playing Text-Adventure Games with Graph-Based Deep Reinforcement Learning (2018, background): “A growing body of research has explored the challenges associated with text-based games (Bordes et al., 2010; Narasimhan et al., 2015; He et al., 2016; Fulda et al., 2017; Haroush et al., 2018; Cˆot´e et al., 2018; Tao et al., 2018).”
Finding "It": Weakly-Supervised Reference-Aware Visual Grounding in Instructional Videos (2018, background): “During training, we leverage the Stanford CoreNLP parser [30] to automatically parse entities.”
Statistical Language Models Based on Neural Networks (2012, background): “For example, it might be important to learn the language together with observing the real world (or simulated world) situations [10].”