Search Results for author:
Found 23 papers, 9 papers with code
RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation
The task of repository-level code completion is to continue writing the unfinished code based on a broader context of the repository.
Exploring Distributional Shifts in Large Language Models for Code Analysis
We systematically study how three large language models with code capabilities - CodeT5, Codex, and ChatGPT - generalize to out-of-domain data.
Generation-Augmented Query Expansion For Code Retrieval
Pre-trained language models have achieved promising success in code retrieval tasks, where a natural language documentation query is given to find the most relevant existing code snippet.
HyperTuning: Toward Adapting Large Language Models without Back-propagation
Fine-tuning large language models for different tasks can be costly and inefficient, and even methods that reduce the number of tuned parameters still require full gradient-based optimization.
AMD-DBSCAN: An Adaptive Multi-density DBSCAN for datasets of extremely variable density
DBSCAN has been widely used in density-based clustering algorithms.
Explanations from Large Language Models Make Small Reasoners Better
Integrating free-text explanations to in-context learning of large language models (LLM) is shown to elicit strong reasoning capabilities along with reasonable explanations.
OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering
The information in tables can be an important complement to text, making table-based question answering (QA) systems of great value.
Ranked #8 on
Semantic Parsing
on WikiTableQuestions
An End-to-End Dialogue Summarization System for Sales Calls
Summarizing sales calls is a routine task performed manually by salespeople.
Knowledge-Grounded Dialogue Generation with a Unified Knowledge Representation
To address these challenges, we present PLUG, a language model that homogenizes different knowledge sources to a unified knowledge representation for knowledge-grounded dialogue generation tasks.
A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation
Large pretrained generative models like GPT-3 often suffer from hallucinating non-existent or incorrect content, which undermines their potential merits in real applications.
Finetuning Pretrained Transformers into RNNs
Specifically, we propose a swap-then-finetune procedure: in an off-the-shelf pretrained transformer, we replace the softmax attention with its linear-complexity recurrent alternative and then finetune.
Ranked #2 on
Machine Translation
on WMT2017 Chinese-English
Linear Polarization of the 21 cm Line from the Epoch of Reionization
The 21 cm linear polarization due to Thomson scattering off free electrons can probe the distribution of neutral hydrogen in the intergalactic medium during the epoch of reionization, complementary to the 21 cm temperature fluctuations.
Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics
The impact of inhomogeneous subgrid clumping on cosmic reionization II: modelling stochasticity
Unresolved fluctuations in numerical simulations and analytical calculations are included using a gas clumping factor, typically assumed to be independent of the local environment.
Cosmology and Nongalactic Astrophysics
Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning
In contrast to existing paradigms, our approach uses knowledge graphs implicitly, only during pre-training, to inject language models with structured knowledge via learning from raw text.
Estimation of HII Bubble Size Distribution from 21cm Power Spectrum with Artificial Neural Networks
The bubble size distribution of ionized hydrogen regions probes the information about the morphology of \HII\ bubbles during the reionization.
Cosmology and Nongalactic Astrophysics
Conditional Self-Attention for Query-based Summarization
Thereby, the contextual dependencies modeled by CSA will be highly relevant to the query.
X-SQL: reinforce schema representation with context
In this work, we present X-SQL, a new network architecture for the problem of parsing natural language to SQL query.
IncSQL: Training Incremental Text-to-SQL Parsers with Non-Deterministic Oracles
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.
Robust Text-to-SQL Generation with Execution-Guided Decoding
We consider the problem of neural semantic parsing, which translates natural language questions into executable SQL queries.
Action-dependent Control Variates for Policy Optimization via Stein Identity
Policy gradient methods have achieved remarkable successes in solving challenging reinforcement learning problems.
Action-depedent Control Variates for Policy Optimization via Stein's Identity
Policy gradient methods have achieved remarkable successes in solving challenging reinforcement learning problems.
Learning from the Wisdom of Crowds by Minimax Entropy
We propose a minimax entropy principle to improve the quality of these labels.
