Paper (2604.20065) argues LLM agents will reshape personalization, proposing 'governable personalization'.

Columbia professor publishes argument that LLMs are fundamentally limited for scientific discovery due to their interpolation-based architecture.

New mechanistic studies confirm LLMs exhibit sycophancy as core reasoning behavior, not a superficial bug

Research shows LLMs can de-anonymize users from public data trails, breaking traditional anonymity assumptions

Researchers proposed training framework for formal counterexample generation in Lean 4, addressing neglected skill in mathematical AI.

Research paper proposing VLM2Rec framework to fix modality collapse in multimodal recommendation systems was posted on arXiv.

Research reveals LLMs can 'self-purify' against poisoned data in RAG systems, identifying and down-ranking falsehoods

Research paper published introducing VLM2Rec framework to fix modality collapse in VLMs for sequential recommendation

Research paper 'VLM4Rec: Multimodal Semantic Representation for Recommendation with Large Vision-Language Models' posted to arXiv