• 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

1

『模型』

• 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?

2

『文本生成』

• 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

3

『机器翻译』

• 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

4

『对话与问答』

• 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

5

『知识与推理』

• 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

6

『多模态』

• 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

7

『信息检索』

• 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

8

『代码』

• 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

9

『数学』

• Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions
• Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

10

『知识蒸馏』

• 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

11

『表示学习』

• 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

12

『可解释性』

• ORCA: Interpreting Prompted Language Models via Locating Supporting Evidence in the Ocean of Pretraining Data
• ContraSim -- A Similarity Measure Based on Contrastive Learning

13

『鲁棒性』

• Learning from Others: Similarity-based Regularization for Mitigating Artifacts
• Randomized Smoothing with Masked Inference for Adversarially Robust NLP Systems

14

『其他任务』

• 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