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Found 10 papers, 5 papers with code
ProCQA: A Large-scale Community-based Programming Question Answering Dataset for Code Search
Retrieval-based code question answering seeks to match user queries in natural language to relevant code snippets.
Advancing GenAI Assisted Programming--A Comparative Study on Prompt Efficiency and Code Quality Between GPT-4 and GLM-4
Our GenAI Coding Workshop highlights the effectiveness and accessibility of the prompting methodology developed in this study.
Large Language Models in Mental Health Care: a Scoping Review
Objective: The growing use of large language models (LLMs) stimulates a need for a comprehensive review of their applications and outcomes in mental health care contexts.
Text Representation Distillation via Information Bottleneck Principle
Pre-trained language models (PLMs) have recently shown great success in text representation field.
Language Models are Universal Embedders
As such cases span from English to other natural or programming languages, from retrieval to classification and beyond, it is desirable to build a unified embedding model rather than dedicated ones for each scenario.
Towards General Text Embeddings with Multi-stage Contrastive Learning
We present GTE, a general-purpose text embedding model trained with multi-stage contrastive learning.
Challenging Decoder helps in Masked Auto-Encoder Pre-training for Dense Passage Retrieval
Recently, various studies have been directed towards exploring dense passage retrieval techniques employing pre-trained language models, among which the masked auto-encoder (MAE) pre-training architecture has emerged as the most promising.
Improving Large Language Models for Clinical Named Entity Recognition via Prompt Engineering
Results: Using baseline prompts, GPT-3. 5 and GPT-4 achieved relaxed F1 scores of 0. 634, 0. 804 for MTSamples, and 0. 301, 0. 593 for VAERS.
Learning Diverse Document Representations with Deep Query Interactions for Dense Retrieval
In this paper, we propose a new dense retrieval model which learns diverse document representations with deep query interactions.
Improving Streaming End-to-End ASR on Transformer-based Causal Models with Encoder States Revision Strategies
Firstly, we introduce a real-time encoder states revision strategy to modify previous states.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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