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From Text to Tables: Feature Engineering with LLMs for Tabular Data
While large language models (LLMs) are typically used for conversational purposes in use cases that...
From terabytes to insights: Real-world AI obervability architecture
GUEST: Consider maintaining and developing an e-commerce platform that processes millions of transactions every minute...
From Surveys to Narratives: Rethinking Cultural Value Adaptation in LLMs
arXiv:2505.16408v2 Announce Type: replace Abstract: Adapting cultural values in Large Language Models (LLMs) presents significant...
From Roots to Rewards: Dynamic Tree Reasoning with Reinforcement Learning
arXiv:2507.13142v3 Announce Type: replace-cross Abstract: Modern language models address complex questions through chain-of-thought (CoT) reasoning...
From RLHF to Direct Alignment: A Theoretical Unification of Preference Learning for Large Language Models
arXiv:2601.06108v1 Announce Type: cross Abstract: Aligning large language models (LLMs) with human preferences has become...
From prompt chaos to clarity: How to build a robust AI orchestration layer
Choosing orchestration frameworks can be overwhelming, but some experts believe there are best practices to...
From Pretraining to Post-Training: Why Language Models Hallucinate and How Evaluation Methods Reinforce the Problem
Large language models (LLMs) very often generate “hallucinations”—confident yet incorrect outputs that appear plausible. Despite...
From Perception to Action: The Role of World Models in Embodied AI Systems
Introduction to Embodied AI Agents Embodied AI agents are systems that exist in physical or...
From Interpretability to Performance: Optimizing Retrieval Heads for Long-Context Language Models
arXiv:2601.11020v1 Announce Type: new Abstract: Advances in mechanistic interpretability have identified special attention heads, known...
From integration chaos to digital clarity: Nutrien Ag Solutions’ post-acquisition reset
Thank you for joining us on the “Enterprise AI hub.” In this episode of the...
From Individuals to Interactions: Benchmarking Gender Bias in Multimodal Large Language Models from the Lens of Social Relationship
arXiv:2506.23101v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have shown impressive capabilities across...
From In-Silico to Wet-Lab: Evaluating AI Protein Design Performance
In this tutorial, we use Anthropic’s claude-protein-binder-design dataset, which contains 1,440 AI-designed miniprotein binders tested...
