Search Results for author: Parisa Kordjamshidi

Found 27 papers, 9 papers with code

Relevant CommonSense Subgraphs for “What if...” Procedural Reasoning

no code implementations Findings (ACL) 2022 Chen Zheng, Parisa Kordjamshidi

We study the challenge of learning causal reasoning over procedural text to answer “What if...” questions when external commonsense knowledge is required.

Relevant CommonSense Subgraphs for "What if..." Procedural Reasoning

1 code implementation21 Mar 2022 Chen Zheng, Parisa Kordjamshidi

We study the challenge of learning causal reasoning over procedural text to answer "What if..." questions when external commonsense knowledge is required.

Zero-Shot Compositional Concept Learning

no code implementations ACL (MetaNLP) 2021 Guangyue Xu, Parisa Kordjamshidi, Joyce Y. Chai

In this paper, we study the problem of recognizing compositional attribute-object concepts within the zero-shot learning (ZSL) framework.

Zero-Shot Learning

SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning

no code implementations NAACL 2021 Roshanak Mirzaee, Hossein Rajaby Faghihi, Qiang Ning, Parisa Kordjamshidi

This paper proposes a question-answering (QA) benchmark for spatial reasoning on natural language text which contains more realistic spatial phenomena not covered by prior work and is challenging for state-of-the-art language models (LM).

Question Answering

Relational Gating for "What If" Reasoning

1 code implementation27 May 2021 Chen Zheng, Parisa Kordjamshidi

We propose a novel relational gating network that learns to filter the key entities and relationships and learns contextual and cross representations of both procedure and question for finding the answer.

Towards Navigation by Reasoning over Spatial Configurations

no code implementations ACL (splurobonlp) 2021 Yue Zhang, Quan Guo, Parisa Kordjamshidi

Additionally, the experimental results demonstrate that explicit modeling of spatial semantic elements in the instructions can improve the grounding and spatial reasoning of the model.

From Spatial Relations to Spatial Configurations

no code implementations LREC 2020 Soham Dan, Parisa Kordjamshidi, Julia Bonn, Archna Bhatia, Jon Cai, Martha Palmer, Dan Roth

To exhibit the applicability of our representation scheme, we annotate text taken from diverse datasets and show how we extend the capabilities of existing spatial representation languages with the fine-grained decomposition of semantics and blend it seamlessly with AMRs of sentences and discourse representations as a whole.

Natural Language Understanding

Cross-Modality Relevance for Reasoning on Language and Vision

1 code implementation ACL 2020 Chen Zheng, Quan Guo, Parisa Kordjamshidi

This work deals with the challenge of learning and reasoning over language and vision data for the related downstream tasks such as visual question answering (VQA) and natural language for visual reasoning (NLVR).

Question Answering Visual Question Answering +2

Declarative Learning-Based Programming as an Interface to AI Systems

no code implementations18 Jun 2019 Parisa Kordjamshidi, Dan Roth, Kristian Kersting

Data-driven approaches are becoming more common as problem-solving techniques in many areas of research and industry.

Anaphora Resolution for Improving Spatial Relation Extraction from Text

no code implementations WS 2018 Umar Manzoor, Parisa Kordjamshidi

Spatial relation extraction from generic text is a challenging problem due to the ambiguity of the prepositions spatial meaning as well as the nesting structure of the spatial descriptions.

Relation Extraction

Visually Guided Spatial Relation Extraction from Text

no code implementations NAACL 2018 Taher Rahgooy, Umar Manzoor, Parisa Kordjamshidi

Extraction of spatial relations from sentences with complex/nesting relationships is very challenging as often needs resolving inherent semantic ambiguities.

Activity Recognition Image Captioning +5

Relational Learning and Feature Extraction by Querying over Heterogeneous Information Networks

no code implementations25 Jul 2017 Parisa Kordjamshidi, Sameer Singh, Daniel Khashabi, Christos Christodoulopoulos, Mark Summons, Saurabh Sinha, Dan Roth

In particular, we provide an initial prototype for a relational and graph traversal query language where queries are directly used as relational features for structured machine learning models.

Knowledge Graphs Natural Language Processing +1

Better call Saul: Flexible Programming for Learning and Inference in NLP

1 code implementation COLING 2016 Parisa Kordjamshidi, Daniel Khashabi, Christos Christodoulopoulos, Bhargav Mangipudi, Sameer Singh, Dan Roth

We present a novel way for designing complex joint inference and learning models using Saul (Kordjamshidi et al., 2015), a recently-introduced declarative learning-based programming language (DeLBP).

Natural Language Processing Part-Of-Speech Tagging +2

EDISON: Feature Extraction for NLP, Simplified

no code implementations LREC 2016 Mark Sammons, Christos Christodoulopoulos, Parisa Kordjamshidi, Daniel Khashabi, Vivek Srikumar, Dan Roth

We present EDISON, a Java library of feature generation functions used in a suite of state-of-the-art NLP tools, based on a set of generic NLP data structures.

Natural Language Processing

Deep Embedding for Spatial Role Labeling

no code implementations28 Mar 2016 Oswaldo Ludwig, Xiao Liu, Parisa Kordjamshidi, Marie-Francine Moens

This paper introduces the visually informed embedding of word (VIEW), a continuous vector representation for a word extracted from a deep neural model trained using the Microsoft COCO data set to forecast the spatial arrangements between visual objects, given a textual description.

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