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	A	B	C	D	E	F	G	H	I
1		Paper	Notes	Video Rec	Date (assigned)	Presenter	Disscusant #1	Disscusant #2	Disscusant #3 (DO NOT SELECT unless there is no other papers.)
2	Classical Reasoning	Programs With Common Sense
3	Classical Reasoning	Some Philosophical Problems From The Standpoint of Artificial Intelligence			02/05	Xiaodong
4	Classical Reasoning	Interpretation as Abduction	Long Version
5	Classical Reasoning	Learning in Order to Reason: The Approach			02/17	Aditya Kashyap
6	Classical Reasoning	Learning to Reason: The Non-Monotonic Case
7	Classical Reasoning	Position Paper on Common-sense and Formal Semantics
8	Classical Reasoning	Intelligence without representation			02/17	Arun
9	Classical Reasoning	Fusion, Propagation, and Structuring in Belief Networks
10	Classical Reasoning	REVEREND BAYES ON INFERENCE ENGINES: A DISTRIBUTED HIERARCHICAL APPROACH
11	Classical Reasoning	Probabilistic (logic) programming concepts	CO 11, 12
12	Classical Reasoning	Probabilistic Logic Programming and Bayesian Networks	CO 11, 12
13	Classical Reasoning	Robust logics
14	Classical Reasoning	Jack and Janet in Search of a Theory of Knowledge
15	Classical Reasoning	The Art and Science of Cause and Effect			02/05	Sihao
16	Theory	Learning Abductive Reasoning Using Random Examples
17	Framework	Learning and Inference with Constraints	CO 17, 18
18	Framework	Structured Learning with Constrained Conditional Models	CO 17, 18		03/04	Sihao	Xinran	Xiaodong
19	Framework	Markov logic networks
20	Framework	Posterior Regularization for Structured Latent Variable Models
21	Framework	Global Reasoning over Database Structures for Text-to-SQL Parsing			02/19	George
22	Framework	A Linear Programming Formulation for Global Inference in Natural Language Tasks			02/26	Aditya Kashyap	George	Kaifu
23	Framework	Memory Networks	CT 23,24,25,27
24	Framework	Neural Turing Machines	CT 23,24,25,27
25	Framework	Ask Me Anything: Dynamic Memory Networks for Natural Language Processing	CT 23,24,25,27		02/24	Yijie Zhao	Qiao	Weiyu
26	Framework	Learning to Compose Neural Networks for Question Answering			02/19	Kaifu	Xiaodong	Qiao
27	Framework	Compositional Attention Networks for Machine Reasoning	CT 23,24,25,27		02/24	Weiyu	Arun	Saket
28	Symbolic, Graph & Structure	A Joint Model for Extended Semantic Role Labeling			04/20	Leon	Yijie Zhao	Haoyu
29	Symbolic, Graph & Structure	Global machine learning for spatial ontology population
30	Symbolic, Graph & Structure	Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision			02/26	Qiao	Yijie Zhao	Kaifu
31	Symbolic, Graph & Structure	Global Learning of Focused Entailment Graphs
32	Symbolic, Graph & Structure	Joint Reasoning for Temporal and Causal Relations			03/02	Haoyu	Sihao	Anushree
33	Symbolic, Graph & Structure	Question Answering as Global Reasoning over Semantic Abstractions			03/02	Xiaodong	Anushree
34	Probabilistic Reasoning	Montague Meets Markov: Deep Semantics with Probabilistic Logical Form
35	Probabilistic Reasoning	On the Proper Treatment of Quantifiers in Probabilistic Logic Semantics
36	Probabilistic Reasoning	Representing Meaning with a Combination of Logical and Distributional Models			03/04	Michal P	Krunal
37	Probing & Position	Ordinal Common-sense Inference	CT 37,38,39
38	Probing & Position	The Winograd Schema Challenge	CT 37,38,39		03/23	Harry	Yijie Zhao	Sihao
39	Probing & Position	Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks	CT 37,38,39		03/23	Arun	Yijie Zhao	Saket	Michal P
40	Probing & Position	What Can Neural Networks Reason About?	CT 40,41,42		03/25	Anushree	George	Michal P	Qiao
41	Probing & Position	Measuring abstract reasoning in neural networks	CT 40,41,42		03/25	Xinran	Xiaodong	Haoyu
42	Probing & Position	Can Neural Networks Understand Logical Entailment?	CT 40,41,42
43	Logics in NN	SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver
44	Logics in NN	Augmenting Neural Networks with First-order Logic
45	Logics in NN	DeepLogic: Towards End-to-End Differentiable Logical Reasoning
46	Logics in NN	Logical Rule Induction and Theory Learning Using Neural Theorem Proving	CO 46,48		03/18	Kaifu	Anushree	Krunal
47	Logics in NN	A Semantic Loss Function for Deep Learning with Symbolic Knowledge			03/18	Qiao	Weiyu	Anushree
48	Logics in NN	End-to-End Differentiable Proving	CO 46,48
49	Logics in NN	Harnessing Deep Neural Networks with Logic Rules			03/30	Weiyu	Xiaodong	Qiao
50	QA	Combining Natural Logic and Shallow Reasoning for Question Answering			03/30	Saket	Leon	Weiyu
51	QA	Question Answering via Integer Programming over Semi-Structured Knowledge			04/01	Haoyu	Leon	Aditya Kashyap
52	QA	Multi-hop Reading Comprehension through Question Decomposition and Rescoring			04/01	George	Saket	Leon
53	QA	Neural Module Networks for Reasoning over Text	DNS
54	QA	Exploring Markov Logic Networks for Question Answering			04/06	Leon	George	Haoyu	Michal P
55	QA	What’s Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering			04/06	Krunal	Saket	Aditya Kashyap
56	QA	Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering			04/08	Anushree	Xinran	Aditya Kashyap
57	QA	DIFFERENTIABLE REASONING OVER A VIRTUAL KNOWLEDGE BASE			04/08	Michal P	Leon	Weiyu
58	Math Problems	Mapping to Declarative Knowledge for Word Problem Solving			04/13	Yijie Zhao	Arun	George	Harry
59	Math Problems	Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension			04/13	Krunal	Arun	Xinran	Harry
60	Math Problems	Analysing Mathematical Reasoning Abilities of Neural Models			04/15	Xinran	Kaifu	Aditya Kashyap	Harry
61	Definitions / Few shot	Joint Concept Learning and Semantic Parsing from Natural Language Explanations			04/15	Saket	Haoyu	Kaifu	Harry
62	Definitions / Few shot	Extracting Commonsense Properties from Embeddings with Limited Human Guidance			04/20	Harry	Arun	Xinran
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