Увеличение производительности

Answering natural language questions us- ing the Freebase knowledge base has re- cently been explored as a platform for ad- vancing the state of the art in open do- main …...

It is well known that prosodic information is used by infants in early language acquisition. In particular, prosodic boundaries have been shown to help infants with sentence and word- level …...

Given a pair of sentences, we present com- putational models to assess if one sentence is simpler to read than the other. While ex- isting models explored the usage of …...

We describe a technique for adding contex- tual distinctions to word embeddings by ex- tending the usual embedding process — into two phases. The first phase resembles existing methods, but …...

This paper explores the task of translating nat- ural language queries into regular expressions which embody their meaning. In contrast to prior work, the proposed neural model does not utilize …...

AbstractTo enable human-robot communication and collaboration, previous works represent grounded verb semantics as the potential change of state to the physical world caused by these verbs. Grounded verb semantics are …...

AbstractCoreference evaluation metrics are hard to optimize directly as they are non-differentiable functions, not easily decomposable into elementary decisions. Consequently, most approaches optimize objectives only indirectly related to the end …...

AbstractGiven a sentence and its relevant answer, how to ask good questions is a challenging task, which has many real applications. Inspired by human’s paraphrasing capability to ask questions of …...

AbstractRecently, the focus of dialogue state tracking has expanded from single domain to multiple domains. The task is characterized by the shared slots between domains. As the scenario gets more …...

Despite recent progress, learning new tasks through language instructions remains an ex- tremely challenging problem. On the AL- FRED benchmark for task learning, the pub- lished state-of-the-art system only achieves …...

AbstractThe existence of multiple datasets for sarcasm detection prompts us to apply transfer learning to exploit their commonality. The adversarial neural transfer (ANT) framework utilizes multiple loss terms that encourage …...

Recently, knowledge graph (KG) augmented models have achieved noteworthy success on various commonsense reasoning tasks. How- ever, KG edge (fact) sparsity and noisy edge extraction/generation often hinder mod- els from …...

AbstractRecently, knowledge distillation (KD) has shown great success in BERT compression. Instead of only learning from the teacher’s soft label as in conventional KD, researchers find that the rich information …...

AbstractProper noun compounds, e.g., “Covid vaccine”, convey information in a succinct manner (a “Covid vaccine” is a “vaccine that immunizes against the Covid disease”). These are commonly used in short-form …...

AbstractHow to learn highly compact yet effective sentence representation? Pre-trained language models have been effective in many NLP tasks. However, these models are often huge and produce large sentence embeddings. …...

AbstractExisting self-supervised learning strategies are constrained to either a limited set of objectives or generic downstream tasks that predominantly target uni-modal applications. This has isolated progress for imperative multi-modal applications …...

AbstractParaphrase identification involves identifying whether a pair of sentences express the same or similar meanings. While cross-encoders have achieved high performances across several benchmarks, bi-encoders such as SBERT have been …...

AbstractHate speech detection is complex; it relies on commonsense reasoning, knowledge of stereotypes, and an understanding of social nuance that differs from one culture to the next. It is also …...