internal representation

Probing Internal Representations of Multi-Word Verbs in Large Language Models NAACL 2025 Unsupervised Hallucination Detection by Inspecting Reasoning Processes EMNLP 2025 When Format Changes Meaning: Investigating Semantic Inconsistency of Large Language Models EMNLP 2025 When Truthful Representations Flip Under Deceptive Instructions? EMNLP 2025 Decoding Probing: Revealing Internal Linguistic Structures in Neural Language Models Using Minimal Pairs COLING 2024 Do Androids Know They’re Only Dreaming of Electric Sheep? ACL 2024 Do Llamas Work in English? On the Latent Language of Multilingual Transformers ACL 2024 Non-Linear Inference Time Intervention: Improving LLM Truthfulness Interspeech 2024 On the Universal Truthfulness Hyperplane Inside LLMs EMNLP 2024 Personalized Speech Enhancement Without a Separate Speaker Embedding Model Interspeech 2024 The Hidden Language of Diffusion Models ICLR 2024 Unlocking the Future: Exploring Look-Ahead Planning Mechanistic Interpretability in Large Language Models EMNLP 2024 Actionable Neural Representations: Grid Cells from Minimal Constraints ICLR 2023 Class Incremental Learning for Task-Oriented Dialogue System with Contrastive Distillation on Internal Representations (Student Abstract) AAAI 2023 Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness? EMNLP 2023 Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task ICLR 2023 Internal Robust Representations for Domain Generalization AAAI 2023 Analyzing Gender Representation in Multilingual Models ACL 2022 Language Models Understand Us, Poorly EMNLP 2022 LM-Debugger: An Interactive Tool for Inspection and Intervention in Transformer-Based Language Models EMNLP 2022 On the Symmetries of Deep Learning Models and their Internal Representations NeurIPS 2022 What Does My GNN Really Capture? On Exploring Internal GNN Representations IJCAI 2022 Model Selection for Cross-lingual Transfer EMNLP 2021 How Accents Confound: Probing for Accent Information in End-to-End Speech Recognition Systems ACL 2020 How does BERT’s attention change when you fine-tune? An analysis methodology and a case study in negation scope ACL 2020