All Updates
Page 1454 of 1462
February 12, 2026
LLMs Accelerate Systematic Mapping
Experience report on using LLMs for systematic mapping studies. Highlights time savings in screening and extraction but notes challenges like hallucinations and prompt engineering. Offers lessons and recommendations for adoption.
LLM Evolutionary Sampling Speeds Databases
DBPlanBench exposes physical query plans for LLM-proposed localized edits, refined via evolutionary search. LLMs leverage semantic knowledge for optimizations like join orderings. Achieves up to 4.78x speedups, with transfers from small to large databases.
LLM Agents Auto-Optimize RecSys Models
A self-evolving system uses Google's Gemini LLMs to autonomously generate, train, and deploy recommendation model improvements. It features an Offline Agent for hypothesis generation and an Online Agent for production validation. Deployed successfully at YouTube, surpassing manual workflows.
LITT: Timing Transformer for EHR Events
LITT introduces a Timing-Transformer architecture that aligns sequential events on a virtual relative timeline for event-timing-focused attention. It enables personalized clinical trajectory interpretations. Validated on EHR data from 3,276 breast cancer patients to predict cardiotoxicity onset.
Latent Flows Model Reaction Trajectories
LatentRxnFlow predicts reactions as continuous latent trajectories via Conditional Flow Matching from reactant-product pairs. Offers SOTA USPTO accuracy with trajectory diagnostics and uncertainty estimation. Enables error mitigation and reliable predictions.
Large-Scale AI Social Simulation Launched
AIvilization v0 deploys a resource-constrained artificial society with unified LLM agents. Features hierarchical planning, adaptive profiles, and human steering for long-horizon autonomy. Reproduces real market stylized facts like wealth stratification.
LAP Achieves Zero-Shot Robot Embodiment Transfer
Language-Action Pre-training (LAP) represents robot actions in natural language for zero-shot transfer across embodiments without fine-tuning. LAP-3B, a 3B VLA, delivers over 50% success on novel robots and tasks. Enables efficient adaptation and unifies action prediction with VQA.
LakeMLB Benchmarks ML in Data Lakes
LakeMLB is a benchmark for machine learning in data lakes, focusing on multi-table union and join scenarios with real datasets from government, finance, and more. Supports pre-training, augmentation strategies. Evaluates tabular ML methods and releases datasets/code.
KSTER Attacks Reverse LLM Model Edits
KSTER exploits low-rank updates in locate-then-edit methods to recover edited data via spectral keyspace reconstruction and entropy prompt recovery. Achieves high success on multiple LLMs. Defense subspace camouflage uses decoys to hide fingerprints.
KPO Stabilizes LLM Policy Optimization
Online Causal Kalman Filtering models IS ratios as evolving latent states for stable RL in LLMs. Smooths noise while preserving token structure. Superior on math reasoning datasets.
KG-Guided LLM for SSD Analysis
KORAL integrates LLMs with Data and Literature Knowledge Graphs for SSD diagnostics from fragmented telemetry. Provides descriptive, predictive, prescriptive, what-if analysis with explainable insights. Outperforms expert methods on production traces.
ImprovEvolve Boosts AlphaEvolve Solutions
Enhances LLM-guided evolution by evolving programs that propose, improve, and perturb solutions iteratively. Achieves new SOTA on hexagon packing and autocorrelation inequality benchmarks. Reduces LLM cognitive load via structured parameterization.
HZO Speeds Zeroth-Order Optimization
Hierarchical Zero-Order optimization decomposes network depth for efficient ZO in DNNs. Reduces query complexity from O(ML^2) to O(ML log L). Matches backpropagation accuracy on CIFAR-10 and ImageNet.
Human Guidance Excels in Vibe Coding
Presents experimental framework comparing human-led, AI-led, and hybrid vibe coding groups. Humans deliver superior iterative instructions, preventing AI-led performance collapse. Hybrids thrive with human direction and AI evaluation.
Guide Transitions Orgs to Agentic AI
Practical framework shifts organizations to agentic AI via domain-driven tasks and human-in-loop orchestration. Addresses challenges like workflow ownership and scaling. Emphasizes small AI-augmented teams with business alignment.
GTR Enhances Time Series Forecasting
Global Temporal Retriever (GTR) is a plug-and-play module extending MTSF models' context via global pattern retrieval. Uses adaptive embeddings, dynamic alignment, and 2D convolution fusion. SOTA results on six datasets with low overhead; code on GitHub.
GRU-Mem Optimizes Long-Context LLM Reasoning
GRU-Mem introduces text-controlled gates to MemAgent for efficient long-context reasoning, preventing memory explosion and unnecessary computation. Update and exit gates manage recurrent memory loops via RL rewards. Achieves up to 400% faster inference on reasoning tasks.
Generative Framework for Brain Infarct Masks
Introduces an anatomy-preserving method using VAE and latent diffusion to generate multi-class brain segmentation masks from NCCT data. It learns anatomical latents from masks only, generating realistic samples with optional lesion control. Avoids artifacts seen in pixel-space models.
GenAI Framework for Higher Ed
Surveys reveal divided stakeholder perceptions of GenAI in IT/EE disciplines at University of Oulu. Proposes conceptual framework with high-level requirements for responsible integration. Ensures EU AI Act compliance and addresses privacy, integrity concerns.
GameDevBench Evaluates Game Dev Agents
GameDevBench offers 132 multimodal game development tasks from tutorials. Agents struggle, with top solving 54.5%; tasks demand code and asset handling. Simple image/video feedback improves performance up to 47.7%.