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Multi-Task Learning

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하위 태스크: 2
평가표: 8
보존된 평가 기록: 16

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.

<span style="color:grey; opacity: 0.6">( Image credit: Cross-stitch Networks for Multi-task Learning )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/eunseongc/mgfid

공식 코드

Multi-Granularity Guided Fusion-in-Decoder

https://github.com/event-ahu/openpar

공식 코드

SequencePAR: Understanding Pedestrian Attributes via A Sequence Generation Paradigm

https://github.com/exploration-lab/hldc

공식 코드

HLDC: Hindi Legal Documents Corpus

https://github.com/exploration-lab/iitk-semeval-2024-task-4-pursuasion-techniques

공식 코드

IITK at SemEval-2024 Task 4: Hierarchical Embeddings for Detection of Persuasion Techniques in Memes

https://github.com/exploration-lab/mutec

공식 코드

Multi-Task Learning Framework for Extracting Emotion Cause Span and Entailment in Conversations

https://github.com/facebookresearch/GraphLog

공식 코드

Evaluating Logical Generalization in Graph Neural Networks

https://github.com/facebookresearch/SentEval

공식 코드

Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning

https://github.com/facebookresearch/adatt

공식 코드

AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations

https://github.com/facebookresearch/atlas

공식 코드

Atlas: Few-shot Learning with Retrieval Augmented Language Models

https://github.com/facebookresearch/llama

공식 코드

LLaMA: Open and Efficient Foundation Language Models

https://github.com/facebookresearch/llama-hd-dataset

공식 코드

Multi-Task Learning for Front-End Text Processing in TTS

https://github.com/facebookresearch/metaicl

공식 코드

MetaICL: Learning to Learn In Context

https://github.com/facebookresearch/mmf/tree/main/projects/unit

공식 코드

UniT: Multimodal Multitask Learning with a Unified Transformer

https://github.com/facebookresearch/mtenv

공식 코드

Multi-Task Reinforcement Learning with Context-based Representations

https://github.com/facebookresearch/mtrl

공식 코드

Multi-Task Reinforcement Learning with Context-based Representations

https://github.com/facebookresearch/slip

공식 코드

SLIP: Self-supervision meets Language-Image Pre-training

https://github.com/fajri91/indommlu

공식 코드

Large Language Models Only Pass Primary School Exams in Indonesia: A Comprehensive Test on IndoMMLU

https://github.com/feichtenhofer/twostreamfusion

공식 코드

Two-Stream Convolutional Networks for Action Recognition in Videos

https://github.com/feiliu36/mtnco

공식 코드

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization

https://github.com/felixwzh/tsgb

공식 코드

Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction

https://github.com/fengranmark/convrelexpand

공식 코드

Learning to Relate to Previous Turns in Conversational Search

https://github.com/fengxiaoming520/rlministyler

공식 코드

RLMiniStyler: Light-weight RL Style Agent for Arbitrary Sequential Neural Style Generation

https://github.com/feyzaakyurek/bbnli

공식 코드

On Measuring Social Biases in Prompt-Based Multi-Task Learning

https://github.com/firojalam/medic

공식 코드

MEDIC: A Multi-Task Learning Dataset for Disaster Image Classification

https://github.com/fkirste/gem_emnlp2022-toasts

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Analyzing Multi-Task Learning for Abstractive Text Summarization

https://github.com/flak300S/emnlp2020_CNE-net

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A Multi-Task Incremental Learning Framework with Category Name Embedding for Aspect-Category Sentiment Analysis

https://github.com/flcao/CoFED

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Cross-Silo Heterogeneous Model Federated Multitask Learning

https://github.com/formiel/fairseq

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Pre-training for Speech Translation: CTC Meets Optimal Transport

https://github.com/frankaging/dancing-in-chains

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Dancing in Chains: Reconciling Instruction Following and Faithfulness in Language Models

https://github.com/fraunhoferhhi/soloplanes

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Multi-task Planar Reconstruction with Feature Warping Guidance

https://github.com/frb-yousefi/aggregated-multitask-gp

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Multi-task Learning for Aggregated Data using Gaussian Processes

https://github.com/fredzzhang/atlas

공식 코드

Knowledge Composition using Task Vectors with Learned Anisotropic Scaling

https://github.com/fudan-zvg/ego3rt

공식 코드

Learning Ego 3D Representation as Ray Tracing

https://github.com/fundamentalvision/Uni-Perceiver

공식 코드

Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks

https://github.com/fuyuanlyu/htlnet

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Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation

https://github.com/fyubang/direct-ie

공식 코드

Adjacency List Oriented Relational Fact Extraction via Adaptive Multi-task Learning

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