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Found 12 papers, 1 papers with code
Language Model Augmented Monotonic Attention for Simultaneous Translation
The state-of-the-art adaptive policies for Simultaneous Neural Machine Translation (SNMT) use monotonic attention to perform read/write decisions based on the partial source and target sequences.
Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy
Modern LLM architectures treat all inputs equally, failing to distinguish between and prioritize various types of instructions, such as system messages, user prompts, and data.
Improving Multilingual Instruction Finetuning via Linguistically Natural and Diverse Datasets
Advancements in Large Language Models (LLMs) have significantly enhanced instruction-following capabilities.
WPO: Enhancing RLHF with Weighted Preference Optimization
This method not only addresses the distributional gap problem but also enhances the optimization process without incurring additional costs.
Learning without Forgetting: Task Aware Multitask Learning for Multi-Modality Tasks
Inspired by these learning patterns in humans, we suggest a simple yet generic task aware framework to incorporate into existing joint learning strategies.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
End-to-End Simultaneous Translation System for IWSLT2020 Using Modality Agnostic Meta-Learning
In this paper, we describe end-to-end simultaneous speech-to-text and text-to-text translation systems submitted to IWSLT2020 online translation challenge.
End-to-End Offline Speech Translation System for IWSLT 2020 using Modality Agnostic Meta-Learning
In this paper, we describe the system submitted to the IWSLT 2020 Offline Speech Translation Task.
Ranked #3 on
Speech-to-Text Translation
on MuST-C EN->DE
(using extra training data)
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+7
Small energy masking for improved neural network training for end-to-end speech recognition
More specifically, a time-frequency bin is masked if the filterbank energy in this bin is less than a certain energy threshold.
Look Harder: A Neural Machine Translation Model with Hard Attention
Soft-attention based Neural Machine Translation (NMT) models have achieved promising results on several translation tasks.
MemoReader: Large-Scale Reading Comprehension through Neural Memory Controller
Machine reading comprehension helps machines learn to utilize most of the human knowledge written in the form of text.
Ranked #36 on
Question Answering
on TriviaQA
(using extra training data)
Cut to the Chase: A Context Zoom-in Network for Reading Comprehension
In recent years many deep neural networks have been proposed to solve Reading Comprehension (RC) tasks.
Ranked #4 on
Question Answering
on NarrativeQA
A Multi-Stage Memory Augmented Neural Network for Machine Reading Comprehension
Reading Comprehension (RC) of text is one of the fundamental tasks in natural language processing.
Ranked #69 on
Question Answering
on SQuAD1.1
