Optimizing Context Management in Long-Running Multi-Agent Systems with Slack
Optimizing Long-Running Agent Systems: Insights from Slack's Approach to Context Management In the fast-evolving landscape of AI-driven communication, ensuring productivity…
Cross-Lingual Benchmark for Token-Level Recognition of Semantic Differences: A Human-Annotated Approach
SwissGov-RSD: Advancing Semantic Difference Recognition in Cross-Lingual Contexts In the ever-evolving landscape of natural language processing (NLP), the capability to…
Integrating AutoRegressive and Diffusion Vision-Language Models through Efficient Progressive Block Merging and Stage-Wise Distillation Techniques
BARD: Bridging AutoRegressive and Diffusion Vision-Language Models In the realm of artificial intelligence, particularly in vision-language models (VLMs), a pressing…
Exploring Reasoning, Instruction, and Source Memory in Large Language Model Hallucinations
Understanding PRISM: A Breakthrough in Evaluating Large Language Model Hallucinations Recently, the field of artificial intelligence has witnessed remarkable advancements,…
Uber Successfully Transitions Over 75,000 Test Classes from JUnit 4 to JUnit 5 with Automated Code Transformation
Migrating from JUnit 4 to JUnit 5: Uber's Strategic Leap Forward In an impressive feat of engineering prowess, Uber has…
Comprehensive Multilingual and Multimodal Medical Examination Dataset for Effective Language Model Evaluation
EuropeMedQA Study Protocol: A Breakthrough in Multilingual Medical AI In the rapidly evolving landscape of artificial intelligence (AI), particularly in…
QCon San Francisco 2026: Explore 12 Newly Announced Tracks for Tech Innovators
As we step into 2026, the landscape of engineering has evolved dramatically, necessitating that senior engineers tackle increasingly complex challenges.…
How Shared Lexical Task Representations Influence Behavioral Variability in Large Language Models (LLMs)
Understanding Prompt Sensitivity in Large Language Models: Insights from arXiv:2604.22027v1 Large Language Models (LLMs) have revolutionized various fields, but they…
Enhanced Physical Reasoning: Integrating Large Language Models with Physics Engines for Parameter Identification
LLMPhy: Revolutionizing Physical Reasoning through Large Language Models and Physics Engines In the rapidly evolving field of artificial intelligence, the…
![Understanding How Learning Rate Decay Can Waste Valuable Data in Curriculum-Based LLM Pretraining: Insights from [2511.18903]](https://aimodelkit.com/wp-content/uploads/2026/04/1777269648_arxiv-logo-fb-330x220.png "Understanding How Learning Rate Decay Can Waste Valuable Data In Curriculum-Based Llm Pretraining: Insights From [2511.18903]"){kind=logo}
Understanding How Learning Rate Decay Can Waste Valuable Data in Curriculum-Based LLM Pretraining: Insights from [2511.18903]
How Learning Rate Decay Wastes Your Best Data in Curriculum-Based LLM Pretraining In the rapidly evolving field of machine learning,…
