#large language models
Large Language Models: 89 AI articles covering large language models news, analysis, and research
Articles
Unhealthy LLM Use Is More Common Than You Think⭐9
A recent study finds nearly 40% of regular users exhibit unhealthy LLM habits, from social replacement to anxiety, revealing problematic AI use is more common t...
Guarantees on Dynamical System Distinguishability for LLM Token⭐8
DS-based LLM output detection achieves exponential error decay with sequence length, formalized via spectral distance between linear dynamical systems.
Imbalanced Data Clustering via Targeted Data Augmentation Using⭐7
Explore a novel method combining GMMs and LLMs for targeted data augmentation, improving clustering on imbalanced text datasets by enriching underrepresented cl...
LLM Framework for Discovering Major Mathematical Conjectures:⭐8
LLM-driven three-stage pipeline for discovering major mathematical conjectures, combining region search, reflective validation, and Lean 4 formal proof to
Can AI Evaluate AI Scientists? A Benchmarking Study of⭐9
Benchmarking AI Scientist systems via automated multi-model review reveals FARS papers score 2x higher across originality, rigor, clarity, and significance.
Prompt Chaining in Practice: A Case Study in Automated Scholarly⭐9
Prompt chaining boosts reliability to 100% vs 50% for single-shot LLMs in scholarly report generation, with higher ROUGE-L F1 (0.507 vs 0.486).
Prompt Engineering vs Loop Engineering vs Graph Engineering:⭐8
Prompt, loop, and graph engineering are distinct layers of AI control: one response, one agent cycle, and multi-agent orchestration, each building on the last.
Knowledge-guided Disentanglement with Atomic Actions for Action⭐9
Proposes KDA, using LLMs to decompose actions into atomic actions with spatial-temporal semantics for enhanced, disentangled action recognition, achieving
Intra-Paper Claim Verification for Peer Review: Do Methods⭐9
A framework for intra-paper claim verification in peer review, assessing if methods support stated novelty claims using LLMs and reviewer-inspired criteria.
AI Book Burning? Companies Are Destroying Millions of Books to⭐9
Companies are destroying millions of physical books to train AI chatbots, sparking ethical, environmental, and copyright concerns in 2026.