negative log-likelihood

d-itlab at SemEval-2026 Task 12: Per-Option Surprisal and Multi-Stage Gating for Precision-Oriented Causal Reasoning SemEval 2026 Preference Optimization via Contrastive Divergence: Your Policy Is Secretly an NLL Estimator AAAI 2026 AnoLLM: Large Language Models for Tabular Anomaly Detection ICLR 2025 Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting ICML 2025 Flexible Copula-Based Mixed Models in Deep Learning: A Scalable Approach to Arbitrary Marginals AISTATS 2025 Improving Diversity in Language Models: When Temperature Fails, Change the Loss ICML 2025 More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives ACL 2025 Reassessing How to Compare and Improve the Calibration of Machine Learning Models ICLR 2025 SketchDNN: Joint Continuous-Discrete Diffusion for CAD Sketch Generation ICML 2025 TempTest: Local Normalization Distortion and the Detection of Machine-generated Text AISTATS 2025 Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive? ICML 2025 Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling NeurIPS 2024 Observation-Guided Diffusion Probabilistic Models CVPR 2024 On the Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization EACL 2024 TIC-TAC: A Framework For Improved Covariance Estimation In Deep Heteroscedastic Regression ICML 2024 MDPose: real-time multi-person pose estimation via mixture density model UAI 2023 On the inconsistency of separable losses for structured prediction EACL 2023 RewardsOfSum: Exploring Reinforcement Learning Rewards for Summarisation ACL 2021 Symbolic Music Generation with Transformer-GANs AAAI 2021 Probabilistic Orientation Estimation with Matrix Fisher Distributions NeurIPS 2020 Information Theoretic lower bounds on negative log likelihood ICLR 2019 Learning RBM with a DC programming Approach ACML 2017