Applications
MoE for Drift-Aware Malicious Traffic Detection
MalMoE detects encrypted malicious traffic using graph-based Mixture-of-Experts to handle graph drift. It selects optimal 1-hop-GNN experts via a redesigned gate model.
ArXiv AI · 217d ago
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Page 1367 of 1372
February 12, 2026
Models
MLLMs Survey on Chart Fusion
Survey organizes MLLM evolution for chart understanding via multimodal fusion. Introduces taxonomy of tasks and datasets.
ArXiv AI · 217d ago
Research
MIPLIB-NL for Industrial Optimization Benchmarks
MIPLIB-NL creates natural-language optimization benchmarks from real MIPLIB 2017 instances via structure-aware reverse engineering. Includes 223 validated reconstructions tying NL specs to solver code.
ArXiv AI · 217d ago
Image
MetaphorStar Masters Image Metaphor Reasoning
MetaphorStar uses end-to-end visual RL for image metaphor understanding, featuring TFQ-Data dataset, TFQ-GRPO method, and TFQ-Bench. MetaphorStar-32B sets SOTA on implication benchmarks, outperforming 20+ MLLMs including Gemini-3.0-pro.
ArXiv AI · 217d ago
Models
MERIT Boosts LLM Negotiation Skills
AgoraBench tests LLMs in nine bargaining scenarios like deception; utility metrics measure human alignment. MERIT feedback via prompting/finetuning elicits deeper strategy and opponent awareness.
ArXiv AI · 217d ago
Models
MEL Boosts LLM Reasoning via Meta-Experience
Meta-Experience Learning (MEL) enhances RLVR by internalizing error-derived meta-experience into LLM memory. Uses self-verification for contrastive analysis of trajectories.
ArXiv AI · 217d ago
Image
MeCSAFNet Boosts Multispectral Segmentation
MeCSAFNet uses dual ConvNeXt encoders for visible and non-visible channels in multispectral land cover segmentation. It employs smooth attentional feature fusion with CBAM and ASAU activation.
ArXiv AI · 217d ago
Models
LRMs Fail to Transfer Reasoning to ToM
Study compares reasoning vs non-reasoning LLMs on ToM benchmarks, finding no consistent gains and sometimes worse performance. Insights reveal slow thinking collapse, need for adaptive reasoning, and option-matching shortcuts.
ArXiv AI · 217d ago
Research
LOREN: Low-Rank Adaptation for Neural Receivers
LOREN introduces low-rank adapters to enable code-rate adaptation in neural receivers without storing separate weights. It freezes a shared base network and trains lightweight adapters per code rate.
ArXiv AI · 217d ago
Models
LoRA Enables Modular Chemistry Prediction
Evaluates LoRA for parameter-efficient fine-tuning of LLMs on organic reaction datasets like USPTO and C-H functionalisation. Matches full fine-tuning accuracy while preserving multi-task performance and mitigating forgetting.
ArXiv AI · 217d ago
Models
Locomo-Plus Tests LLM Cognitive Memory
Locomo-Plus benchmarks cognitive memory in LLM agents under cue-trigger disconnects, focusing on latent conversational constraints. It proposes constraint consistency evaluation over string-matching.
ArXiv AI · 217d ago
Models
LLMs Tackle Agent-Based Model Replication
Study evaluates 17 LLMs on ODD-to-Python code generation for predator-prey model. Assesses executability, fidelity, efficiency via NetLogo baseline.
ArXiv AI · 217d ago
Applications
LLMs Predict Stroke Outcomes from Notes
Fine-tuned LLMs like Llama predict mRS scores from admission notes alone. Achieves 33.9% exact 90-day accuracy and 76.3% binary, matching structured baselines.
ArXiv AI · 217d ago
Models
LLMs Outstrategize Humans in Games
Uses AlphaEvolve to discover interpretable models of human and LLM strategic behavior from data. Analysis on iterated rock-paper-scissors shows frontier LLMs capable of deeper strategy than humans.
ArXiv AI · 217d ago
Models
LLMs Generate Planning Abstractions
Prompts pretrained LLMs to create QNP abstractions for generalized planning from domains and tasks. Automated debugging detects/fixes errors iteratively.
ArXiv AI · 217d ago
Models
LLMs Fail Cultural Recipes
LLMs generate culturally unrepresentative recipe adaptations unlike humans. Outputs ignore cultural distance correlations from GlobalFusion dataset.
ArXiv AI · 217d ago
Models
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.
ArXiv AI · 217d ago
Models
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.
ArXiv AI · 217d ago
Models
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.
ArXiv AI · 217d ago
Applications
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.
ArXiv AI · 217d ago
Applications
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.
ArXiv AI · 217d ago
Models
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.
ArXiv AI · 217d ago
Applications
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.
ArXiv AI · 217d ago
Research
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.
ArXiv AI · 217d ago
Models
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.
ArXiv AI · 217d ago
Models
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.
ArXiv AI · 217d ago
Applications
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.
ArXiv AI · 217d ago
Coding
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.
ArXiv AI · 217d ago
Infrastructure
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).
ArXiv AI · 217d ago
Coding
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.
ArXiv AI · 217d ago