Predicting information pathways across online communities
The problem of community-level information pathway prediction (CLIPP) aims at predicting
the transmission trajectory of content across online communities. A successful solution to …
the transmission trajectory of content across online communities. A successful solution to …
Complex query answering on eventuality knowledge graph with implicit logical constraints
Querying knowledge graphs (KGs) using deep learning approaches can naturally leverage
the reasoning and generalization ability to learn to infer better answers. Traditional neural …
the reasoning and generalization ability to learn to infer better answers. Traditional neural …
BRAINTEASER: Lateral Thinking Puzzles for Large Language Model
The success of language models has inspired the NLP community to attend to tasks that
require implicit and complex reasoning, relying on human-like commonsense mechanisms …
require implicit and complex reasoning, relying on human-like commonsense mechanisms …
Acquiring and modeling abstract commonsense knowledge via conceptualization
Conceptualization, or viewing entities and situations as instances of abstract concepts in
mind and making inferences based on that, is a vital component in human intelligence for …
mind and making inferences based on that, is a vital component in human intelligence for …
Intentionqa: A benchmark for evaluating purchase intention comprehension abilities of language models in e-commerce
Enhancing Language Models'(LMs) ability to understand purchase intentions in E-
commerce scenarios is crucial for their effective assistance in various downstream tasks …
commerce scenarios is crucial for their effective assistance in various downstream tasks …
Knowcomp at semeval-2023 task 7: Fine-tuning pre-trained language models for clinical trial entailment identification
In this paper, we present our system for the textual entailment identification task as a subtask
of the SemEval-2023 Task 7: Multi-evidence Natural Language Inference for Clinical Trial …
of the SemEval-2023 Task 7: Multi-evidence Natural Language Inference for Clinical Trial …
MARS: Benchmarking the metaphysical reasoning abilities of language models with a multi-task evaluation dataset
To enable Large Language Models (LLMs) to function as conscious agents with
generalizable reasoning capabilities, it is crucial that they possess the reasoning ability to …
generalizable reasoning capabilities, it is crucial that they possess the reasoning ability to …
KnowComp at DialAM-2024: Fine-tuning Pre-trained Language Models for Dialogical Argument Mining with Inference Anchoring Theory
In this paper, we present our framework for DialAM-2024 TaskA: Identification of
Propositional Relations and TaskB: Identification of Illocutionary Relations. The goal of task …
Propositional Relations and TaskB: Identification of Illocutionary Relations. The goal of task …
Miko: Multimodal Intention Knowledge Distillation from Large Language Models for Social-Media Commonsense Discovery
Social media has become ubiquitous for connecting with others, staying updated with news,
expressing opinions, and finding entertainment. However, understanding the intention …
expressing opinions, and finding entertainment. However, understanding the intention …
Gold: A global and local-aware denoising framework for commonsense knowledge graph noise detection
Commonsense Knowledge Graphs (CSKGs) are crucial for commonsense reasoning, yet
constructing them through human annotations can be costly. As a result, various automatic …
constructing them through human annotations can be costly. As a result, various automatic …