[PDF] Top 20 Explain Yourself! Leveraging Language Models for Commonsense Reasoning
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Explain Yourself! Leveraging Language Models for Commonsense Reasoning
... tween sentences and how that interacts with world knowledge. For example, the Winograd Schemas (Winograd, 1972) and challenges derived from that format (Levesque et al., 2012; McCann et al., 2018; Wang et al., 2018) have ... See full document
11
CoRg: Commonsense Reasoning Using a Theorem Prover and Machine Learning
... Commonsense reasoning is an everyday task that is intuitive for humans but hard to implement for ...the reasoning process remains a black ...conducted models will be analyzed using machine ... See full document
7
KagNet: Knowledge Aware Graph Networks for Commonsense Reasoning
... Commonsense reasoning aims to empower machines with the human ability to make presumptions about ordinary situations in our daily ...ing commonsense questions, which effec- tively utilizes external, ... See full document
11
IIT KGP at COIN 2019: Using pre trained Language Models for modeling Machine Comprehension
... pretrained Language Models alone can model commonsense reasoning better than the other models incorporating com- monsense knowledge base resources like Concept- Net, NELL, etc ... See full document
5
Attention Is (not) All You Need for Commonsense Reasoning
... several language un- derstanding ...attention-guided commonsense reasoning method is conceptu- ally simple yet empirically ...monsense reasoning tasks might require more than unsupervised ... See full document
6
Reasoning with Heterogeneous Knowledge for Commonsense Machine Comprehension
... with commonsense knowl- edge is critical for natural language un- ...for commonsense machine comprehension mostly only focus on one specific kind of knowledge, neglecting the fact that ... See full document
12
A Hybrid Neural Network Model for Commonsense Reasoning
... neural language models trained on large amounts of text ...neural language model trained on raw text from books and news to calculate the probabilities of the natural language sentences which ... See full document
9
Towards Generalizable Neuro Symbolic Systems for Commonsense Question Answering
... multi-hop commonsense relation paths from ConceptNet and proposed to inject common- sense knowledge into neural models’ intermedi- ate representations, using ...QA models to make the final ...based ... See full document
11
Social IQa: Commonsense Reasoning about Social Interactions
... for commonsense reasoning about social ...collect commonsense questions along with correct and incorrect answers about social interac- tions, using a new framework that mitigates stylistic artifacts ... See full document
11
Language, logic and ontology: uncovering the structure of commonsense knowledge
... of commonsense, most readers would find no difficulty in a reading for (1a) that implies John’s support for the ‘same’ activist in every ...our commonsense knowledge of how the world (the possible world we ... See full document
26
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning
... our models with the un- supervised baselines, ELMo (Peters et ...Google Language Model for commonsense rea- soning (Trinh and Le, 2018), which compares the perplexities of the new sentences by ... See full document
10
PP 2003 06: Rational Dynamics and Epistemic Logic in Games
... Dynamic intuitions concerning activities of deliberation and communication lie behind much of epistemic logic and related themes in game theory — though they are often implicit. In physics, an equilibrium is only ... See full document
34
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning
... The vast majority (93.8%) of our dataset re- quires contextual commonsense reasoning, in con- trast with existing machine comprehension (MRC) datasets such as SQuAD (Rajpurkar et al., 2016), RACE (Lai et ... See full document
11
Visual Choice of Plausible Alternatives: An Evaluation of Image based Commonsense Causal Reasoning
... this reasoning, the state-of-the-art, called CausalNet (Luo et ...desirable reasoning ability should be required not only in KR domain but also in Computer Vi- sion (CV) ... See full document
5
Estimating Future Health Technology Diffusion Using Expert Beliefs Calibrated to an Established Diffusion Model
... Introduction Introduce yourself Explain that the aim is to quantify beliefs about future purchases of Technology A for PTB screening in the UK Explain that this study will inform a[r] ... See full document
31
Commonsense reasoning about processes: a study of ideas about reversibility.
... Another two aspects can be analysed: firstly, the notably goal-like feature of this event for the Brazilian 16/17 group is shown by the positive frequency of replies to Phrases 7 - 'fo[r] ... See full document
423
Commonsense Knowledge Mining from Pretrained Models
... using language models for tasks requiring com- monsense, such as the Story Cloze Task and the Winograd Schema Challenge, respectively (Mostafazadeh et ...unidirectional language models for ... See full document
6
The Lacunae of Danish Natural Language Processing
... Germanic language spoken principally in Denmark, a coun- try with a long tradition of technologi- cal and scientific ...the language has received relatively lit- tle attention from a technological perspec- ... See full document
7
The Commonsense Algorithm as a Basis for Comfuter Models of Human Memory, Inference, Belief and Contextual Language Comprehension
... ... See full document
16
Data Augmentation for Low Resource Neural Machine Translation
... low-resource language pairs. By leveraging language models trained on large amounts of monolingual data, we gen- erate new sentence pairs containing rare words in new, synthetically created ... See full document
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