Shashank Srivastava

I am a graduate student at Carnegie Mellon University. I like statistical learning, language, AI and story-telling. I also like Escher prints.

My doctoral advisor is Tom Mitchell, and my dissertation research focuses on helping machines learn from natural language interaction. I have previously worked on models of computational semantics with Ed Hovy and emergence of compositional language in artificial agents with Harish Karnick.

I graduated from Indian Institute of Technology, Kanpur. Once upon a time, I did bad things with other people's money at Tower Research Capital.

Curriculum Vitae

I am co-organizing a workshop on Learning by Instruction at NIPS 2018

Selected Publications:

  • Teaching Machines to Classify from Natural Language Interactions

S Srivastava

PhD Thesis, CMU 2018


  • A Spatial Model for Extracting and Visualizing Latent Discourse Structure in Text

S Srivastava, N Jojic

ACL 2018

  • Zero-shot Learning of Classifiers from Natural Language Quantification

S Srivastava, I Labutov, T Mitchell

ACL 2018

  • LIA: A Natural Language Programmable Personal Assistant

I Labutov, S Srivastava, T Mitchell

EMNLP 2018 (System Demos)

Media coverage

  • Where have I heard this story before? : Identifying Narrative Similarity in Movie Remakes'

S Chaturvedi, S Srivastava, D Roth

NAACL 2018 (short)

  • Learning Classifiers from Declarative Language

S Srivastava, I Labutov, T Mitchell

NIPS Workshop on Learning from Limited Data 2017

  • Joint Concept Learning and Semantic Parsing from Natural Language Explanations

S Srivastava, I Labutov, T Mitchell

EMNLP 2017

  • Parsing Natural Language Conversations with Contextual Cues

S Srivastava, A Azaria, T Mitchell

IJCAI 2017

  • Inferring Interpersonal Relations in Narrative Summaries

S Srivastava, S Chaturvedi, T Mitchell

AAAI 2016

Media coverage

  • Modeling Evolving Relationships Between Characters in Literary Novels

S Chaturvedi, S Srivastava, H Daume, C Dyer

AAAI 2016

  • CMU-ML System for KBP Cold Start Slot Filling

B Kisiel, B McDowell, M Gardner, N Nakashole, E Platanios, A Saparov, S Srivastava, D Wijaya, T Mitchell

TAC 2015

  • Vector-space semantics with frequency driven motifs

S Srivastava, E Hovy

ACL 2014

  • Spatial Compactness meets Topical Consistency: Jointly modeling link and content for community detection

M Sachan, A Dubey, S Srivastava, EP Xing, E Hovy

WSDM 2014

  • A Semantically Enriched Tree Kernel Over Distributed Word Representations

S Srivastava, D Hovy, E Hovy

EMNLP 2013 (short)

  • A Structured Distributional Semantic Model for Event Co-reference

K Goyal*, S Jauhar*, H Li*, M Sachan*, S Srivastava*, E Hovy

ACL 2013 (short)

(* equally contributing)

  • Identifying Metaphorical Word Use with Tree Kernels

D Hovy, S Srivastava, S Jauhar, M Sachan, K Goyal, H Li, E Hovy

NAACL-HLT Meta4NLP Workshop 2013

  • A Structured Distributional Semantic Model : Integrating Structure with Semantics

K Goyal, S Jauhar, S Srivastava, M Sachan, H Li, E Hovy

Workshop on Continuous Vector Space Models and their Compositionality, ACL 2013

  • A Topical graph-kernel for Link Prediction in Labeled Graphs

S Chaturvedi, H Daume III, T Moon, S Srivastava

ICML Workshop on Mining and Learning with Graphs (MLG) 2012

  • Evolution of Compositional Languages in Multiple Agent Social Communities

S Srivastava

MTech Thesis, IIT Kanpur, Sep 2010

  • A Reinforcement learning based Autoguider for Astrophotography

S Srivastava, M Hirsch, J Peters, B Scholkopf

Technical Report, MPI Tuebingen 2009