All Articles
18316 articles total
cAPM: Continual AI-Assisted Pace-Mapping with Active Learning
cAPM introduces a continual learning framework for AI-assisted pace-mapping in cardiac ablation, significantly improving localization accuracy over previous active-learning methods.
Protein Representation Learning with Secondary-Structure and Energy-Filtered Hydrogen-Bond Graphs
The authors propose a secondary-structure-aware graph neural network (SSProNet) for protein representation learning that incorporates hydrogen-bond interactions and structural motifs.
Cost-Optimal LLM Routing with Limited User Feedback under User Satisfaction Guarantees
SLARouter is an online routing algorithm for LLMs that optimizes costs while providing theoretical guarantees for strict Service Level Agreement (SLA) compliance.
Emyx: Fast and efficient all-atom protein generation
Emyx is a lightweight conditional flow matching model for all-atom protein generation that outperforms larger models in enzyme design while requiring significantly less training time.
How Linear Is a Transformer Feed-Forward Block? Per-Block Linear Recoverability Is Learned, Not Architectural
Research exploring the linear recoverability of Transformer Feed-Forward blocks, discovering that linearity is a learned property rather than an architectural one.
Improving Code-Switching ASR with Code-Mixing Guided Synthetic Speech
A new preference-learning framework for improving code-switching ASR by generating synthetic speech with better language-boundary consistency.
DynAMO:Dynamic Asset Management Orchestration via Topological Multi-Agent Scheduling
DynAMO is an orchestration engine for LLM-powered industrial agents that uses a Plan-then-Execute architecture to improve efficiency and safety in Industry 4.0.
Bistable by Construction: Wall-Clock-Calibrated State Monitors Have No Moment-Detection Regime at Agent Cadence
A technical correction and analysis of runtime monitors for autonomous agents, highlighting how wall-clock calibration leads to failure in moment-detection regimes.
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
DeepSeek-V4 introduces MoE language models supporting 1 million token context with improvements in attention architecture and a new Muon optimizer.
Where to Place the Query? Unveiling and Mitigating Positional Bias in In-Context Learning for Diffusion LLMs via Decoding Dynamics
Research on Diffusion LLMs reveals that query position significantly impacts In-Context Learning quality, proposing Auto-ICL for adaptive query routing.
Detecting Hallucinations for Large Language Model-based Knowledge Graph Reasoning
LUCID is proposed as a hallucination detection method for LLM-based knowledge graph reasoning, integrating attention scores and KG structure.
Sign-Language Datasets at Scale: A Comprehensive Survey on Resources, Benchmarks, and Annotation Standards
A comprehensive survey on sign-language datasets and the release of a standardized documentation repository for inclusive technology development.
Trustworthy Multi-Agent Systems: Mitigating Semantic Drift with the Argent Signaling Protocol
The Argent Signaling Protocol (ASP) introduces structured quality signals to multi-agent LLM systems to distinguish and handle different failure types.
Physical Atari: A Robust and Accessible Platform for Real-time Reinforcement Learning on Robots
Physical Atari is an accessible, low-cost hardware platform for real-time reinforcement learning on robots using a physical Atari controller.
Computational Identifiability
The paper proposes 'computational identifiability' to replace theoretical identifiability with a finite computational search procedure for empirical estimators.
Information Lattice Learning as Probabilistic Graphical Model Structure Learning
Research explores Information Lattice Learning (ILL) as a method for probabilistic graphical model structure learning for interpretable rules.
Zero-Inflated Gaussian Distributions Enable Parameter-Space Sparsity in Estimation-of-Distribution Algorithms
A new EDA approach uses zero-inflated Gaussian distributions to enable parameter-space sparsity in black-box optimization.
Human-like autonomy emerges from self-play and a pinch of human data
A method combining minimal human data with self-play reinforcement learning is shown to emerge human-like driving autonomy efficiently.
Fable Converted Pylint to Rust
Fable has rewritten Pylint, a popular Python linter, in Rust to improve performance.
The Raku Foundation is born
The Raku Foundation has been established to support the development and governance of the Raku programming language.