Search Results for author: Oleksandr Polozov

Found 16 papers, 8 papers with code

Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions

1 code implementation28 May 2022 Ansong Ni, Jeevana Priya Inala, Chenglong Wang, Oleksandr Polozov, Christopher Meek, Dragomir Radev, Jianfeng Gao

We show that our use of self-sampled correct and partially-correct solutions can benefit learning and help guide the sampling process, leading to more efficient exploration of the solution space.

Arithmetic Reasoning Efficient Exploration +2

Synchromesh: Reliable code generation from pre-trained language models

no code implementations ICLR 2022 Gabriel Poesia, Oleksandr Polozov, Vu Le, Ashish Tiwari, Gustavo Soares, Christopher Meek, Sumit Gulwani

Then, Synchromesh feeds the examples to a pre-trained language model and samples programs using Constrained Semantic Decoding (CSD): a general framework for constraining the output to a set of valid programs in the target language.

Code Generation Language Modelling

KaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers

1 code implementation ACL 2021 Chia-Hsuan Lee, Oleksandr Polozov, Matthew Richardson

The goal of database question answering is to enable natural language querying of real-life relational databases in diverse application domains.

Question Answering SQL Parsing +1

Programming Puzzles

2 code implementations10 Jun 2021 Tal Schuster, Ashwin Kalyan, Oleksandr Polozov, Adam Tauman Kalai

The dataset is comprehensive in that it spans problems of a range of difficulties and domains, ranging from trivial string manipulation problems, to classic programming puzzles (e. g., Tower of Hanoi), to interview/competitive-programming problems (e. g., dynamic programming), to longstanding open problems in algorithms and mathematics (e. g., factoring).

Code Generation Natural Language Understanding +1

Structure-Grounded Pretraining for Text-to-SQL

no code implementations NAACL 2021 Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, Oleksandr Polozov, Huan Sun, Matthew Richardson

Additionally, to evaluate different methods under more realistic text-table alignment settings, we create a new evaluation set Spider-Realistic based on Spider dev set with explicit mentions of column names removed, and adopt eight existing text-to-SQL datasets for cross-database evaluation.


Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"

no code implementations ICML 2020 Saeed Amizadeh, Hamid Palangi, Oleksandr Polozov, Yichen Huang, Kazuhito Koishida

To address this, we propose (1) a framework to isolate and evaluate the reasoning aspect of VQA separately from its perception, and (2) a novel top-down calibration technique that allows the model to answer reasoning questions even with imperfect perception.

Graph Generation Question Answering +4

RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers

4 code implementations ACL 2020 Bailin Wang, Richard Shin, Xiaodong Liu, Oleksandr Polozov, Matthew Richardson

The generalization challenge lies in (a) encoding the database relations in an accessible way for the semantic parser, and (b) modeling alignment between database columns and their mentions in a given query.

Semantic Parsing Text-To-SQL


no code implementations25 Sep 2019 Ashwin Kalyan, Oleksandr Polozov, Adam Tauman Kalai

Puzzles are objective in that one can easily test the correctness of a given solution x by seeing whether it satisfies f, unlike the most common representations for program synthesis: given input-output pairs or an English problem description, the correctness of a given solution is not determined and is debatable.

Program Synthesis

Program Synthesis and Semantic Parsing with Learned Code Idioms

1 code implementation NeurIPS 2019 Richard Shin, Miltiadis Allamanis, Marc Brockschmidt, Oleksandr Polozov

Program synthesis of general-purpose source code from natural language specifications is challenging due to the need to reason about high-level patterns in the target program and low-level implementation details at the same time.

Code Generation Program Synthesis +1

IncSQL: Training Incremental Text-to-SQL Parsers with Non-Deterministic Oracles

no code implementations13 Sep 2018 Tianze Shi, Kedar Tatwawadi, Kaushik Chakrabarti, Yi Mao, Oleksandr Polozov, Weizhu Chen

We present a sequence-to-action parsing approach for the natural language to SQL task that incrementally fills the slots of a SQL query with feasible actions from a pre-defined inventory.

Action Parsing Text-To-SQL

Robust Text-to-SQL Generation with Execution-Guided Decoding

1 code implementation9 Jul 2018 Chenglong Wang, Kedar Tatwawadi, Marc Brockschmidt, Po-Sen Huang, Yi Mao, Oleksandr Polozov, Rishabh Singh

We consider the problem of neural semantic parsing, which translates natural language questions into executable SQL queries.

Semantic Parsing Text-To-SQL

Generative Code Modeling with Graphs

1 code implementation ICLR 2019 Marc Brockschmidt, Miltiadis Allamanis, Alexander L. Gaunt, Oleksandr Polozov

Generative models for source code are an interesting structured prediction problem, requiring to reason about both hard syntactic and semantic constraints as well as about natural, likely programs.

Structured Prediction

Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples

no code implementations ICLR 2018 Ashwin Kalyan, Abhishek Mohta, Oleksandr Polozov, Dhruv Batra, Prateek Jain, Sumit Gulwani

In this work, we propose Neural Guided Deductive Search (NGDS), a hybrid synthesis technique that combines the best of both symbolic logic techniques and statistical models.

Program Synthesis

FlashProfile: A Framework for Synthesizing Data Profiles

no code implementations17 Sep 2017 Saswat Padhi, Prateek Jain, Daniel Perelman, Oleksandr Polozov, Sumit Gulwani, Todd Millstein

However, manual inspection of data to identify the different formats is infeasible in standard big-data scenarios.

Learning Syntactic Program Transformations from Examples

no code implementations31 Aug 2016 Reudismam Rolim, Gustavo Soares, Loris D'Antoni, Oleksandr Polozov, Sumit Gulwani, Rohit Gheyi, Ryo Suzuki, Bjoern Hartmann

In the second domain, we use repetitive edits applied by developers to the same project to synthesize a program transformation that applies these edits to other locations in the code.

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