https://github.com/qijimrc/robust
공식 코드Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.
Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.
Source: Wikipedia
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction
Syntactically Robust Training on Partially-Observed Data for Open Information Extraction
Leveraging Pre-trained Models for FF-to-FFPE Histopathological Image Translation
Augmenting Biomedical Named Entity Recognition with General-domain Resources
MambaVC: Learned Visual Compression with Selective State Spaces
Semantic-Aware Resource Management for C-V2X Platooning via Multi-Agent Reinforcement Learning
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
SSM-DTA: Breaking the Barriers of Data Scarcity in Drug-Target Affinity Prediction
SSM-DTA: Breaking the Barriers of Data Scarcity in Drug-Target Affinity Prediction
Queue management for slo-oriented large language model serving
BianCang: A Traditional Chinese Medicine Large Language Model
Subjective-Aligned Dataset and Metric for Text-to-Video Quality Assessment
TrafficVLM: A Controllable Visual Language Model for Traffic Video Captioning
DMoERM: Recipes of Mixture-of-Experts for Effective Reward Modeling
RES-Q: Evaluating Code-Editing Large Language Model Systems at the Repository Scale
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
Every Answer Matters: Evaluating Commonsense with Probabilistic Measures
Stateful Memory-Augmented Transformers for Efficient Dialogue Modeling
Collaborative Stance Detection via Small-Large Language Model Consistency Verification
Emotion-Aware Transformer Encoder for Empathetic Dialogue Generation
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning
Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks
Romanian Speech Recognition Experiments from the ROBIN Project
Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis
MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.