All Articles
17889 articles total
Simulation-based inference for rapid Bayesian parameter estimation in epidemiological models: a comparison with MCMC
A study comparing Simulation-based inference (SBI) with MCMC for rapid Bayesian parameter estimation in epidemiological models.
Prompt Injection in Automated R\'esum\'e Screening with Large Language Models: Single and Multi-Injection Settings
Explores the vulnerability of automated LLM-based résumé screening to prompt injection attacks by job applicants.
A Pipeline for Generating Longitudinal Synthetic Clinical Notes Using Large Language Models
A new pipeline for generating longitudinal synthetic clinical notes using LLMs to provide safe, privacy-preserving data for clinical AI development.
Generative Retrieval via Diffusion Transformer with Metric-Ordered Sequence Training and Hybrid-Policy Preference Optimization
Introduction of MO-DiT+HPPO, a framework for pattern-preserving attribute retrieval using Diffusion Transformers and preference optimization.
Learning to Recover Task Experts from a Multi-Task Merged Model
The ReTeX framework allows for the recovery of task-specific expert performance from a single merged model checkpoint by predicting parameter offsets.
Diagnosing Task Insensitivity in Language Agents
Research identifying 'task insensitivity' in LLM agents and proposing Task-Perturbed NLL Optimization to improve OOD generalization.
Where Do CoT Training Gains Land in LLM based Agents?
An investigation into whether CoT training improves the reasoning process or simply the prompt-action prediction quality in LLM agents.
Look-Before-Move: Narrative-Grounded World Visual Attention in Dynamic 3D Story Worlds
The Look-Before-Move framework enables active visual attention and camera planning in dynamic 3D story worlds for embodied AI.
Einstein World Models
Einstein World Models (EWMs) propose using visual-temporal rollouts as visual thought experiments to enhance LLM reasoning.
Adaptive Utility driven Resource Orchestration for Resilient AI (AURORA-AI)
AURORA-AI is an adaptive resource orchestration framework designed to maintain resilient and fair AI deployment under non-stationary conditions.
Semantic Early-Stopping for Iterative LLM Agent Loops
A study on semantic early-stopping for LLM agent loops to reduce token consumption without sacrificing answer quality.
How to evaluate clustering with ground truth?
A review of external validity indexes for evaluating clustering with ground truth, recommending the centroid index (CI).
US Govt to individually approve who gets GPT 5.6
Rumors or discussions regarding US government intervention in the approval process for GPT-5.6 access.
22-year-old Mozart's handwritten notebook unearthed in 'major discovery'
The discovery of a handwritten music notebook by Mozart in a major archaeological/historical finding.
Micron locks in historically high memory prices for five years
Micron's strategy to secure high memory prices through long-term contracts.
KARLA: Knowledge-base Augmented Retrieval for Language Models
Introduction of KARLA, a method for LLMs to pull factual knowledge from external databases during token generation to improve accuracy and transparency.
Computational Analysis of Heart Rate Variability in Healthy Adults
A study evaluating various Heart Rate Variability (HRV) indices to improve clinical utility and standardization for healthy adults.
The Capability Frontier: Benchmarks Miss 82% of Model Performance
The 'Capability Frontier' paper argues that current benchmarks significantly underestimate LLM performance by not accounting for model specialization and optimal generation sampling.
Context-Aware Synthesis of Optimization Pipelines for Warehouse Optimization
An open-source framework, CASOP, for synthesizing and evaluating optimization pipelines for warehouse order fulfillment.
LCAi: Life Cycle Assessment with big data fusion and retrieval-augmented generation-assisted interpretation
LCAi framework uses RAG and big data fusion to assist in interpreting Life Cycle Assessments for environmental impact analysis.