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Found 4 papers, 3 papers with code
Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents
In this work, we introduce LCoW, a framework for Learning language models to Contextualize complex Web pages into a more comprehensible form, thereby enhancing decision making by LLM agents.
Margin Matching Preference Optimization: Enhanced Model Alignment with Granular Feedback
Large language models (LLMs) fine-tuned with alignment techniques, such as reinforcement learning from human feedback, have been instrumental in developing some of the most capable AI systems to date.
Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning
In tabular prediction tasks, tree-based models combined with automated feature engineering methods often outperform deep learning approaches that rely on learned representations.
Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models
To investigate this issue in depth, we introduce the Text-Image Alignment Assessment (TIA2) benchmark, which comprises a diverse collection of text prompts, images, and human annotations.
