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Found 14 papers, 2 papers with code
Boosting Code Summarization by Embedding Code Structures
We find that a program dependency graph (PDG) can represent the structure of a code more effectively.
Generalizable Implicit Hate Speech Detection Using Contrastive Learning
However, it is challenging to identify implicit hate speech in nuance or context when there are insufficient lexical cues.
Self-Training using Rules of Grammar for Few-Shot NLU
We propose to use rules of grammar in self-training as a more reliable pseudo-labeling mechanism, especially when there are few labeled data.
MultiFix: Learning to Repair Multiple Errors by Optimal Alignment Learning
We consider the problem of learning to repair erroneous C programs by learning optimal alignments with correct programs.
ATHENA: Mathematical Reasoning with Thought Expansion
Solving math word problems depends on how to articulate the problems, the lens through which models view human linguistic expressions.
Ranked #1 on
Math Word Problem Solving
on ASDiv-A
Neuro-Symbolic Regex Synthesis Framework via Neural Example Splitting
We tackle the problem of learning regexes faster from positive and negative strings by relying on a novel approach called `neural example splitting'.
LST: Lexicon-Guided Self-Training for Few-Shot Text Classification
Self-training provides an effective means of using an extremely small amount of labeled data to create pseudo-labels for unlabeled data.
ALP: Data Augmentation using Lexicalized PCFGs for Few-Shot Text Classification
Taken together, our contributions on the data augmentation strategies yield a strong training recipe for few-shot text classification tasks.
SplitRegex: Faster Regex Synthesis via Neural Example Splitting
SplitRegex is a divided-and-conquer framework for learning target regexes; split (=divide) positive strings and infer partial regexes for multiple parts, which is much more accurate than the whole string inferring, and concatenate (=conquer) inferred regexes while satisfying negative strings.
Detecting context abusiveness using hierarchical deep learning
Our model outperforms all the previous models for detecting abusiveness in a text data without abusive words.
SoftRegex: Generating Regex from Natural Language Descriptions using Softened Regex Equivalence
We continue the study of generating se-mantically correct regular expressions from natural language descriptions (NL).
Online Infix Probability Computation for Probabilistic Finite Automata
Probabilistic finite automata (PFAs) are com- mon statistical language model in natural lan- guage and speech processing.
OPERA: Reasoning about continuous common knowledge in asynchronous distributed systems
Each event block is signed by the hashes of the creating node and its $k$ peers.
Distributed, Parallel, and Cluster Computing
Incremental Computation of Infix Probabilities for Probabilistic Finite Automata
The problem of computing infix probabilities of strings when the pattern distribution is given by a probabilistic context-free grammar or by a probabilistic finite automaton is already solved, yet it was open to compute the infix probabilities in an incremental manner.
