Eliciting Numerical Predictive Distributions of LLMs Without Autoregression
Fuente:
arXiv
Saved in:
| Main Authors: | Piskorz, Julianna, Kobalczyk, Katarzyna, van der Schaar, Mihaela |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Preference Learning for AI Alignment: a Causal Perspective
by: Kobalczyk, Katarzyna, et al.
Published: (2025)
by: Kobalczyk, Katarzyna, et al.
Published: (2025)
Discovery of Hidden Miscalibration Regimes
by: Kobalczyk, Katarzyna, et al.
Published: (2026)
by: Kobalczyk, Katarzyna, et al.
Published: (2026)
Active Task Disambiguation with LLMs
by: Kobalczyk, Katarzyna, et al.
Published: (2025)
by: Kobalczyk, Katarzyna, et al.
Published: (2025)
Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes
by: Kobalczyk, Katarzyna, et al.
Published: (2024)
by: Kobalczyk, Katarzyna, et al.
Published: (2024)
Towards Automated Knowledge Integration From Human-Interpretable Representations
by: Kobalczyk, Katarzyna, et al.
Published: (2024)
by: Kobalczyk, Katarzyna, et al.
Published: (2024)
The Synergy of LLMs & RL Unlocks Offline Learning of Generalizable Language-Conditioned Policies with Low-fidelity Data
by: Pouplin, Thomas, et al.
Published: (2024)
by: Pouplin, Thomas, et al.
Published: (2024)
Active Timepoint Selection for Learning Measure-Valued Trajectories
by: Huynh, Nicolas, et al.
Published: (2026)
by: Huynh, Nicolas, et al.
Published: (2026)
Hyperparameter Trajectory Inference with Conditional Lagrangian Optimal Transport
by: Amad, Harry, et al.
Published: (2026)
by: Amad, Harry, et al.
Published: (2026)
Not All Explanations for Deep Learning Phenomena Are Equally Valuable
by: Jeffares, Alan, et al.
Published: (2025)
by: Jeffares, Alan, et al.
Published: (2025)
Inverse-RLignment: Large Language Model Alignment from Demonstrations through Inverse Reinforcement Learning
by: Sun, Hao, et al.
Published: (2024)
by: Sun, Hao, et al.
Published: (2024)
Beyond the ATE: Interpretable Modelling of Treatment Effects over Dose and Time
by: Piskorz, Julianna, et al.
Published: (2025)
by: Piskorz, Julianna, et al.
Published: (2025)
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes
by: Seedat, Nabeel, et al.
Published: (2023)
by: Seedat, Nabeel, et al.
Published: (2023)
Language Bottleneck Models for Qualitative Knowledge State Modeling
by: Berthon, Antonin, et al.
Published: (2025)
by: Berthon, Antonin, et al.
Published: (2025)
Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities
by: Sun, Hao, et al.
Published: (2025)
by: Sun, Hao, et al.
Published: (2025)
Simulating Viva Voce Examinations to Evaluate Clinical Reasoning in Large Language Models
by: Chiu, Christopher, et al.
Published: (2025)
by: Chiu, Christopher, et al.
Published: (2025)
Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond
by: Jeffares, Alan, et al.
Published: (2024)
by: Jeffares, Alan, et al.
Published: (2024)
Interpretable Reward Modeling with Active Concept Bottlenecks
by: Laguna, Sonia, et al.
Published: (2025)
by: Laguna, Sonia, et al.
Published: (2025)
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
by: Sun, Hao, et al.
Published: (2023)
by: Sun, Hao, et al.
Published: (2023)
You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling
by: Seedat, Nabeel, et al.
Published: (2024)
by: Seedat, Nabeel, et al.
Published: (2024)
Causal Deep Learning
by: Berrevoets, Jeroen, et al.
Published: (2023)
by: Berrevoets, Jeroen, et al.
Published: (2023)
Large Language Models to Enhance Bayesian Optimization
by: Liu, Tennison, et al.
Published: (2024)
by: Liu, Tennison, et al.
Published: (2024)
Self-Healing Machine Learning: A Framework for Autonomous Adaptation in Real-World Environments
by: Rauba, Paulius, et al.
Published: (2024)
by: Rauba, Paulius, et al.
Published: (2024)
Time Series Diffusion in the Frequency Domain
by: Crabbé, Jonathan, et al.
Published: (2024)
by: Crabbé, Jonathan, et al.
Published: (2024)
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
by: Schweisthal, Jonas, et al.
Published: (2024)
by: Schweisthal, Jonas, et al.
Published: (2024)
Defining Expertise: Applications to Treatment Effect Estimation
by: Hüyük, Alihan, et al.
Published: (2024)
by: Hüyük, Alihan, et al.
Published: (2024)
DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems
by: Seedat, Nabeel, et al.
Published: (2022)
by: Seedat, Nabeel, et al.
Published: (2022)
CliMB: An AI-enabled Partner for Clinical Predictive Modeling
by: Saveliev, Evgeny, et al.
Published: (2024)
by: Saveliev, Evgeny, et al.
Published: (2024)
Improving the Generation and Evaluation of Synthetic Data for Downstream Medical Causal Inference
by: Amad, Harry, et al.
Published: (2025)
by: Amad, Harry, et al.
Published: (2025)
Technical Report: Facilitating the Adoption of Causal Inference Methods Through LLM-Empowered Co-Pilot
by: Berrevoets, Jeroen, et al.
Published: (2025)
by: Berrevoets, Jeroen, et al.
Published: (2025)
Hypothesis Hunting with Evolving Networks of Autonomous Scientific Agents
by: Liu, Tennison, et al.
Published: (2025)
by: Liu, Tennison, et al.
Published: (2025)
AutoPrognosis 2.0: Democratizing Diagnostic and Prognostic Modeling in Healthcare with Automated Machine Learning
by: Imrie, Fergus, et al.
Published: (2022)
by: Imrie, Fergus, et al.
Published: (2022)
Machine Learning with Requirements: a Manifesto
by: Giunchiglia, Eleonora, et al.
Published: (2023)
by: Giunchiglia, Eleonora, et al.
Published: (2023)
GameTalk: Training LLMs for Strategic Conversation
by: Vendrell, Victor Conchello, et al.
Published: (2026)
by: Vendrell, Victor Conchello, et al.
Published: (2026)
When is Off-Policy Evaluation (Reward Modeling) Useful in Contextual Bandits? A Data-Centric Perspective
by: Sun, Hao, et al.
Published: (2023)
by: Sun, Hao, et al.
Published: (2023)
Interpretable DNA Sequence Classification via Dynamic Feature Generation in Decision Trees
by: Huynh, Nicolas, et al.
Published: (2026)
by: Huynh, Nicolas, et al.
Published: (2026)
Reusing Embeddings: Reproducible Reward Model Research in Large Language Model Alignment without GPUs
by: Sun, Hao, et al.
Published: (2025)
by: Sun, Hao, et al.
Published: (2025)
No Equations Needed: Learning System Dynamics Without Relying on Closed-Form ODEs
by: Kacprzyk, Krzysztof, et al.
Published: (2025)
by: Kacprzyk, Krzysztof, et al.
Published: (2025)
Tiny Autoregressive Recursive Models
by: Rauba, Paulius, et al.
Published: (2026)
by: Rauba, Paulius, et al.
Published: (2026)
DAGnosis: Localized Identification of Data Inconsistencies using Structures
by: Huynh, Nicolas, et al.
Published: (2024)
by: Huynh, Nicolas, et al.
Published: (2024)
Influence-Guided Symbolic Regression: Scientific Discovery via LLM-Driven Equation Search with Granular Feedback
by: Saveliev, Evgeny S., et al.
Published: (2026)
by: Saveliev, Evgeny S., et al.
Published: (2026)
Similar Items
-
Preference Learning for AI Alignment: a Causal Perspective
by: Kobalczyk, Katarzyna, et al.
Published: (2025) -
Discovery of Hidden Miscalibration Regimes
by: Kobalczyk, Katarzyna, et al.
Published: (2026) -
Active Task Disambiguation with LLMs
by: Kobalczyk, Katarzyna, et al.
Published: (2025) -
Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes
by: Kobalczyk, Katarzyna, et al.
Published: (2024) -
Towards Automated Knowledge Integration From Human-Interpretable Representations
by: Kobalczyk, Katarzyna, et al.
Published: (2024)