LAVOIR: Teaching a Single-Pass Decision Encoder When and What to Ask with Amortized Value of Information
cs.AI, cs.CL
Submitted: 2026-09-25
Updated: 2026-09-25
Code: https://github.com/AbdelStark/jev-ben
Terminology
Sources
- STaR-GATE: Teaching Language Models to Ask Clarifying Questions
- A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
- Program Synthesis with Large Language Models
- MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
- Training Verifiers to Solve Math Word Problems
- Gemma 4 Technical Report
- Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in Large Language Models
- Measuring a hate speech spectrum with faceted Rasch item response theory and perspective-aware, explainable-by-design deep learning
- CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models
- mmBERT: A Modern Multilingual Encoder with Annealed Language Learning
- RouteLLM: Learning to Route LLMs with Preference Data
- Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- SCX Router: Streaming Zero-Shot Model Selection with a Decoder-KV Classifier and a Real-World Task Ontology
- GLiClass: Generalist Lightweight Model for Sequence Classification Tasks
- Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
- Qwen3 Technical Report
- MoganBert-TR: A Turkish Encoder Foundation Model Trained from Scratch with a CLM-to-MLM Curriculum
- Clarify When Necessary: Resolving Ambiguity Through Interaction with LMs
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