Research & Innovation

Global: New Framework GLOVE Enables Self‑Verification of LLM Memory Without Ground‑Truth Supervision Researchers have introduced the Global Verifier (GLOVE), a framework designed to let large language models (LLMs) assess and…

Global: Principled Framework Boosts Data Efficiency for Large Language Model Fine‑TuningA group of machine‑learning researchers has unveiled a resource‑efficient framework for selecting and reweighting training data in large‑language‑model fine‑tuning. The…

Global: SpikeScore Offers Cross-Domain Hallucination Detection for Large Language ModelsResearchers have introduced a new metric called SpikeScore to identify hallucinated outputs from large language models (LLMs) when the training data…

Global: New Activation Functions Help Preserve Plasticity in Continual Learning ModelsResearchers announced on arXiv in September 2025 that they have identified activation functions as a key factor in mitigating the…

Global: New Multi-Agent Automaton Sets State-of-the-Art in Visual ReasoningA team of computer scientists has introduced a multi‑agent system designed to enhance the interpretability of vision‑language models while reducing hallucinations on…

Global: Study Quantifies LLM Training Startup Overhead and Introduces Bootseer OptimizationResearchers have released a study detailing the hidden costs that occur before large language model (LLM) training jobs begin execution.…

Global: New Memory-Driven Framework Enhances Adaptive GUI AgentsResearchers from the University of Science and Technology, led by Libo Sun, introduced a novel adaptive agent framework called MAGNET on Jan. 27,…

Global: New Code-Driven Framework Boosts Multimodal Table Reasoning AccuracyA recent arXiv preprint details the introduction of CoReTab, a code‑driven reasoning framework designed to improve multimodal table understanding by coupling multi‑step…

Global: Analysis of DDIM Inversion Reveals Latent Noise Correlation Issues Researchers from an unnamed team announced on October 30, 2024, via an arXiv preprint that they have identified a structural…

Global: New Unified Framework Addresses Irregular Time Series ClassificationOn January 27, 2026, researchers Francesco Spinnato and Cristiano Landi released an updated version of their study introducing PYRREGULAR, a comprehensive framework…