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Found 22 papers, 5 papers with code
Unsupervised Learning of Graph from Recipes
We iteratively learn the graph structure and the parameters of a $\mathsf{GNN}$ encoding the texts (text-to-graph) one sequence at a time while providing the supervision by decoding the graph into text (graph-to-text) and comparing the generated text to the input.
PizzaCommonSense: Learning to Model Commonsense Reasoning about Intermediate Steps in Cooking Recipes
Decoding the core of procedural texts, exemplified by cooking recipes, is crucial for intelligent reasoning and instruction automation.
Identifying Linear Relational Concepts in Large Language Models
Transformer language models (LMs) have been shown to represent concepts as directions in the latent space of hidden activations.
Some Options for Instantiation of Bipolar Argument Graphs with Deductive Arguments
Argument graphs provide an abstract representation of an argumentative situation.
A Graphical Formalism for Commonsense Reasoning with Recipes
Whilst cooking is a very important human activity, there has been little consideration given to how we can formalize recipes for use in a reasoning framework.
Neuro-symbolic Commonsense Social Reasoning
We present a novel system for taking social rules of thumb (ROTs) in natural language from the Social Chemistry 101 dataset and converting them to first-order logic where reasoning is performed using a neuro-symbolic theorem prover.
Automated tabulation of clinical trial results: A joint entity and relation extraction approach with transformer-based language representations
However, it relies on labour-intensive systematic reviews, where domain specialists must aggregate and extract information from thousands of publications, primarily of randomised controlled trial (RCT) results, into evidence tables.
Joint Entity and Relation Extraction
named-entity-recognition
+3
Machine Learning for Utility Prediction in Argument-Based Computational Persuasion
and (2) How can we identify for a new user the best utility function from amongst those that we have learned?
Repurposing of Resources: from Everyday Problem Solving through to Crisis Management
Repurposing arises in everyday situations such as finding substitutes for missing ingredients when cooking, or for unavailable tools when doing DIY.
Strategic Argumentation Dialogues for Persuasion: Framework and Experiments Based on Modelling the Beliefs and Concerns of the Persuadee
Persuasion is an important and yet complex aspect of human intelligence.
Polynomial-time Updates of Epistemic States in a Fragment of Probabilistic Epistemic Argumentation (Technical Report)
Probabilistic epistemic argumentation allows for reasoning about argumentation problems in a way that is well founded by probability theory.
Impact of Argument Type and Concerns in Argumentation with a Chatbot
Conversational agents, also known as chatbots, are versatile tools that have the potential of being used in dialogical argumentation.
Non-monotonic Reasoning in Deductive Argumentation
Nonetheless, there are issues in capturing defeasible reasoning in argumentation including choice of base logic and modelling of defeasible knowledge.
Argument Harvesting Using Chatbots
We describe the architecture of the chatbot, provide methods for managing a corpus of arguments and counterarguments, and an evaluation of our approach in a case study concerning attitudes of women to participation in sport.
Domain Modelling in Computational Persuasion for Behaviour Change in Healthcare
At the core of this proposal is an ontology which provides a representation of key factors, in particular kinds of belief, which we have identified in the behaviour change literature as being important in diverse behaviour change initiatives.
Epistemic Graphs for Representing and Reasoning with Positive and Negative Influences of Arguments
Furthermore, the flexibility of the epistemic approach allows us to both model the rationale behind the existing semantics as well as completely deviate from them when required.
Measuring Inconsistency in Argument Graphs
There have been a number of developments in measuring inconsistency in logic-based representations of knowledge.
Empirical Evaluation of Abstract Argumentation: Supporting the Need for Bipolar and Probabilistic Approaches
It is equipped with a wide range of postulates, including those that do not make any restrictions concerning how initial arguments should be viewed, thus potentially being more adequate for handling beliefs of the people that have not fully disclosed their opinions in comparison to Dung's semantics.
Encoding monotonic multi-set preferences using CI-nets: preliminary report
CP-nets and their variants constitute one of the main AI approaches for specifying and reasoning about preferences.
Extraction of evidence tables from abstracts of randomized clinical trials using a maximum entropy classifier and global constraints
An evidence table has columns for the patient group, for each of the interventions being compared, for the criterion for the comparison (e. g. proportion who survived after 5 years from treatment), and for each of the results.
Probabilistic Argumentation with Epistemic Extensions and Incomplete Information
We consider various constraints on the probability assignment.
Analysis of Dialogical Argumentation via Finite State Machines
We also consider how the finite state machines can be analysed, with the minimax strategy being used as an illustration of the kinds of empirical analysis that can be undertaken.
