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ICLR 2023（投稿）｜自然语言处理相关论文分类整理
本文从ICLR 2023 的投稿论文中筛选出了与自然语言处理相关的论文100多篇，并按照研究主题进行分类整理，以供参考。文章也同步发布在AI Box知乎专栏（知乎搜索 AI Box专栏），欢迎大家在知乎专栏的文章下方评论留言，交流探讨！
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模型 文本生成 机器翻译 对话与问答 知识与推理 多模态 信息检索 代码 数学 知识蒸馏 表示学习 可解释性 鲁棒性 其他任务 Benchmark
EIT: Enhanced Interactive Transformer for Sequence Generation Transformers with Multiresolution Attention Heads SaMoE: Parameter Efficient MoE Language Models via Self-Adaptive Expert Combination Sparse MoE with Random Routing as the New Dropout: Training Bigger and Self-Scalable Models
Guess the Instruction! Making Language Models Stronger Zero-Shot Learners LEXA: Language-agnostic Cross-consistency Training for Question Answering Tasks CCT: Cross-consistency training for Clone Detection and Code Search Tasks Large Language Models Can Self-improve Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning PMixUp: Simultaneous Utilization of Part-of-Speech Replacement and Feature Space Interpolation for Text Data Augmentation Self-Consistent Learning: Cooperation between Generators and Discriminators Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning Toward Adversarial Training on Contextualized Language Representation ContraGen: Effective Contrastive Learning For Causal Language Model Language Model Pre-training with Linguistically Motivated Curriculum Learning MLM with Global Co-occurrence Improving Language Model Pretraining with Text Structure Information Learning by Distilling Context MAT: Mixed-Strategy Game of Adversarial Training in Fine-tuning Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks
Prompt Injection: Parameterization of Fixed Inputs Meta-Weighted Language Model Tuning for Augmentation-Enhanced Few-Shot Learning Pre-trained Language Models can be Fully Zero-Shot Learners KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in Low-Resource NLP Contrastive Novelty Learning: Anticipating Outliers with Large Language Models Model ensemble instead of prompt fusion: a sample-specific knowledge transfer method for few-shot prompt tuning Mass-Editing Memory in a Transformer Zemi: Learning Zero-Shot Semi-Parametric Language Models from Multiple Tasks Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models Selective Annotation Makes Language Models Better Few-Shot Learners Generate rather than Retrieve: Large Language Models are Strong Context Generators Ahead-of-Time P-Tuning Can discrete information extraction prompts generalize across language models?
Dynamic Scheduled Sampling with Imitation Loss for Neural Text Generation DiffusER: Diffusion via Edit-based Reconstruction MVP: Multi-task Supervised Pre-training for Natural Language Generation Penalizing the High-likelihood: A Novel Sampling Method for Open-ended Neural Text Generation via Inverse Probability Weighting RainProof: An Umbrella to Shield Text Generator from Out-Of-Distribution Data A Non-monotonic Self-terminating Language Model PromptSum: Planning with Mixed Prompts for Parameter-Efficient Controllable Abstractive Summarization On the Usefulness of Embeddings, Clusters and Strings for Text Generation Evaluation Joint Generator-Ranker Learning for Natural Language Generation Calibrating Sequence likelihood Improves Conditional Language Generation Sequence to sequence text generation with diffusion models Tailoring Language Generation Models under Total Variation Distance Language Models Can See: Plugging Visual Controls in Text Generation Distribution Aware Metrics for Conditional Natural Language Generation PEER: A Collaborative Language Model
Seq2Seq Pre-training with Dual-channel Recombination for Translation Simple and Scalable Nearest Neighbor Machine Translation Fuzzy Alignments in Directed Acyclic Graph for Non-Autoregressive Machine Translation
Towards Boosting the Open-Domain Chatbot with Human Feedback Learning Locality and Isotropy in Dialogue Modeling Knowledge-Consistent Dialogue Generation with Language Models and Knowledge Graphs Complex-Target-Guided Open-Domain Conversation based on offline reinforcement learning
ReAct: Synergizing Reasoning and Acting in Language Models Language model with Plug-in Knowldge Memory Thrust: Adaptively Propels Large Language Models with External Knowledge Self-Consistency Improves Chain of Thought Reasoning in Language Models DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases Least-to-Most Prompting Enables Complex Reasoning in Large Language Models Neuro-Symbolic Procedural Planning with Commonsense Prompting Multimodal Analogical Reasoning over Knowledge Graphs ThinkSum: Probabilistic reasoning over sets using large language models Joint Representations of Text and Knowledge Graphs for Retrieval and Evaluation Rethinking Identity in Knowledge Graph Embedding gGN: learning to represent nodes in directed graphs as low-rank Gaussian distributions Don't Throw Your Old Policies Away: Knowledge-based Policy Recycling Protects Against Adversarial Attacks Measuring and Narrowing the Compositionality Gap in Language Models
CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers CLIP model is an Efficient Continual Learner Language Modelling with Pixels Visual Classification via Description from Large Language Models Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning RelationCLIP: Training-free Fine-grained Visual and Language Concept Matching Contrastive Prompt Tuning Improves Generalization in Vision-Language Models Masked Vision and Language Modeling for Multi-modal Representation Learning UNIFIED-IO: A Unified Model for Vision, Language, and Multi-modal Tasks Visually-augmented pretrained language models for NLP Tasks without Images Music-to-Text Synaesthesia: Generating Descriptive Text from Music Recordings VLG: General Video Recognition with Web Textual Knowledge Dynamic Historical Adaptation for Continual Image-Text Modeling From Images to Textual Prompts: Zero-shot VQA with Frozen Large Language Models NÜWA-LIP: Language-guided Image Inpainting with Defect-free VQGAN Universal Vision-Language Dense Retrieval: Learning A Unified Representation Space for Multi-Modal Retrieval Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language Language-Guided Artistic Style Transfer Using the Latent Space of DALL-E Unified Vision and Language Prompt Learning DrML: Diagnosing and Rectifying Vision Models using Language MaPLe: Multi-modal Prompt Learning Prefix Conditioning Unifies Language and Label Supervision Domain-Unified Prompt Representations for Source-Free Domain Generalization Learning to Decompose Visual Features with Latent Textual Prompts Delving into the Openness of CLIP Cali-NCE: Boosting Cross-modal Video Representation Learning with Calibrated Alignment Dynamic Historical Adaptation for Continual Image-Text Modeling Design of the topology for contrastive visual-textual alignment
Multi-Vector Retrieval as Sparse Alignment Augmenting Zero-shot Dense Retrievers With Plug-in Mixture-of-memories CAMVR: Context-Adaptive Multi-View Representation Learning for Dense Retrieval
Language Models Can Teach Themselves to Program Better Repository-Level Prompt Generation for Large Language Models of Code NAPG: Non-Autoregressive Program Generation for Hybrid Tabular-Textual Question Answering A Simple, Yet Effective Approach to Finding Biases in Code Generation Deep Learning-based Source Code Complexity Prediction FixEval: Execution-based Evaluation of Program Fixes for Competitive Programming Problems InCoder: A Generative Model for Code Infilling and Synthesis Code Translation with Compiler Representations CodeT: Code Generation with Generated Tests Multi-lingual Evaluation of Code Generation Models
Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning
Speed Up Iterative Non-Autoregressive Transformers by Distilling Multiple Steps A comparison of dataset distillation and active learning in text classification Less is More: Task-aware Layer-wise Distillation for Language Model Compression Distilling Text-Image Foundation Models
RankCSE: Unsupervised Sentence Representations Learning via Learning to Rank Neural Embeddings for Text Ranking-Enhanced Unsupervised Sentence Representation Learning Neural Topic Modeling with Embedding Clustering Regularization Counterfactual Contrastive Learning for Robust Text Classification On The Inadequacy of Optimizing Alignment and Uniformity in Contrastive Learning of Sentence Representations
ORCA: Interpreting Prompted Language Models via Locating Supporting Evidence in the Ocean of Pretraining Data ContraSim -- A Similarity Measure Based on Contrastive Learning
Learning from Others: Similarity-based Regularization for Mitigating Artifacts Randomized Smoothing with Masked Inference for Adversarially Robust NLP Systems
Exploring Methods for Parsing Movie Scripts - Feature Extraction for Further Social Injustice Analysis MSQ-BioBERT: Ambiguity Resolution to Enhance BioBERT Medical Question-Answering Compositional Semantic Parsing with Large Language Models AxBERT: An Explainable Chinese Spelling Correction Method Driven by Associative Knowledge Network BED: Boundary-Enhanced Decoder for Chinese Word Segmentation Semi-connected Joint Entity Recognition and Relation Extraction of Contextual Entities in Family History Records
GuoFeng: A Discourse-aware Evaluation Benchmark for Language Understanding, Translation and Generation
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