information loss

Cross-modal Identity Mapping: Minimizing Information Loss in Modality Conversion via Reinforcement Learning CVPR 2026 Aggregation Mechanism Based Graph Heterogeneous Networks Distillation IJCAI 2025 Asymmetric Reinforcing Against Multi-Modal Representation Bias AAAI 2025 Characterizing Mamba’s Selective Memory using Auto-Encoders IJCNLP 2025 Enhancing Pre-trained Representation Classifiability can Boost its Interpretability ICLR 2025 How to Mitigate Information Loss in Knowledge Graphs for GraphRAG: Leveraging Triple Context Restoration and Query-Driven Feedback IJCAI 2025 Incorporating Visual Experts to Resolve the Information Loss in Multimodal Large Language Models IJCAI 2025 Lost in Embeddings: Information Loss in Vision–Language Models EMNLP 2025 A Study on the Information Mechanism of the 3rd Tone Sandhi Rule in Mandarin Disyllabic Words Interspeech 2024 Focus on Your Question! Interpreting and Mitigating Toxic CoT Problems in Commonsense Reasoning ACL 2024 InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification ACL 2024 Ideal Abstractions for Decision-Focused Learning AISTATS 2023 Quantifying Consistency and Information Loss for Causal Abstraction Learning IJCAI 2023 Understanding the Role of Input Token Characters in Language Models: How Does Information Loss Affect Performance? EMNLP 2023 On the Interplay between Information Loss and Operation Loss in Representations for Classification AISTATS 2022 An Uncertainty Principle is a Price of Privacy-Preserving Microdata NeurIPS 2021 Lost in Interpreting: Speech Translation from Source or Interpreter? Interspeech 2021 Whitening and Second Order Optimization Both Make Information in the Dataset Unusable During Training, and Can Reduce or Prevent Generalization ICML 2021 PatchBERT: Just-in-Time, Out-of-Vocabulary Patching EMNLP 2020 Lost in Translation: Analysis of Information Loss During Machine Translation Between Polysynthetic and Fusional Languages COLING 2018 Non-parametric Policy Search with Limited Information Loss JMLR 2017 Random Shifting for CNN: a Solution to Reduce Information Loss in Down-Sampling Layers IJCAI 2017 Distributed Estimation, Information Loss and Exponential Families NeurIPS 2014 A general framework for investigating how far the decoding process in the brain can be simplified NeurIPS 2008