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Field order in serialized structured metadata silently impacts retrieval quality; proposes permutation-invariant fine-tuning to decouple field order from embeddings.
Non-parametric causal diffusion recovery from cross-sectional steady-state data; application to gene expression without requiring longitudinal observation.
MuonSSM stabilizes state space models for long-sequence modeling via momentum pathways and Newton-Schulz transformations on input injections.
HSAP addresses cross-contamination in causal attention for packed sequences by combining sequence parallelism paradigms for hybrid-context LLM training.
Curvature-Weighted Gradient Diversity (CWGD) refines SGD convergence analysis by weighting gradient noise by inverse Hessian to better model effective optimization dynamics.
Study compares nine open-weight LLMs against human participants in networked Prisoner's Dilemma, finding selected models reproduce cooperation macro-dynamics but lack individual fidelity.
Analysis of enterprise tabular data reveals markedly different distributions and performance profiles from public benchmarks for TabPFN, TabICL, and ConTextTab models.
Three-method study across Qwen2.5-Coder-32B, Llama-3.1-8B, and Gemma-3-27B shows internal probes read situation not pre-action intent, limiting misalignment monitoring efficacy.
Online imitation learning for LLM post-training succeeds when student policy class is realizable; error accumulation is not the primary advantage mechanism.
Theoretical analysis proves online minibatch SGD on two-layer ReLU networks prioritizes shortcut spurious features via optimization dynamics on Boolean hypercube XOR data.
FIL Hypothesis challenges Bitter Lesson by arguing inductive biases matter more when feedback loops are long; computation-scale approach fails in slow-feedback domains.
Framework translates natural language system requirements to ATL/A formal specifications for multi-agent systems verification using LLMs.
Enterprise investment in AI is booming. Gartner is calling 2026 an “inflection year” for organizations to align their AI projects with strategic business objectives. As the pressure to prove ROI mounts, executives and technology leaders are looking to agentic AI to drive the measurable financial outcomes their businesses seek. A prime opportunity for AI agents…
Hybrid active-online learning framework for optical network failure detection achieves 97% accuracy querying only 3.4% of streaming samples.
BrainJanus unifies brain encoding, vision, and language in single multimodal model with brain tokenizer for neural-sensory correspondence.
The startup, Proception, is taking a unique approach to collecting training data to tackle one of the hardest problems in robotics: hands.
Industry experience paper catalogs five MCP server architectural patterns across 15 production implementations post-Anthropic November 2024 release.
Reinforcement learning controller for workload shifting in wind-integrated HPC data centers; RL shows credit-assignment problems in minimal test case.
TRACE: RANO 2.0-aligned concept bottleneck model for interpretable 4-class glioblastoma response classification on longitudinal 3D MRI.
DialogPII: multilingual synthetic dialog dataset across eight scenarios for personal information detection and de-identification system evaluation.
CDF-based Sliced Wasserstein distance estimators eliminate sorting requirements and improve data parallelization for optimal transport computation.
Survey of persistent-state LLM agents covering memory, credentials, audit records, and lifecycle governance across six diagnostic axes.
UKRI metascience project compares GPT-4o, Mistral, and DSIT-Taxonomies for research entity extraction from 42 funding proposal abstracts.
ManimAgent: self-evolving multimodal agent with episodic memory bank carries reflection experience across code-generation tasks for scientific visualization.
Rhetor: multi-agent system automates live product demos via web app control, real-time QA, and source-code awareness to replace human presenters.
DreamForge-World 0.1: low-compute world model for real-time interactive simulation on consumer GPUs with keyboard/mouse control and multimodal init.
PromptGNN-sim: bidirectional GNN-LLM fusion framework for text-attributed graph learning via Graph Attention Networks and semantic-structure alignment.
LoRA variants for continual motion-language agents: addresses stability-plasticity tradeoff in bidirectional motion understanding/generation under sequential task learning.
Theory of acceptance in speculative decoding: formalizes greedy/relaxed verification regimes beyond exact distribution preservation for practical LLM inference.
Dual-Reference SFT defends against embedded harmful supervision in benign fine-tuning data via token-level DPO-style contrastive regularization.