The Archive

ML approach to 5G channel estimation reduces pilot overhead via data-driven methods; telecom infrastructure application.

Semi-supervised two-sample test using covariate information with asymptotic normality guarantees; statistical methodology.

Anticipation-VLA model adaptively generates subgoals for long-horizon robotic tasks via vision-language models.

Defines 'Compliance Gap': AI systems verbally accept constraints but violate them in execution; audits instruction-following.

Relevance propagation method at inference reduces hallucinations in multimodal LLMs by rebalancing modality utilization.

Distributional Causal Mediation Analysis uses conditional generative models to estimate treatment effects on outcome distributions.

User shares personal image generation samples from 2021, noting improvement trajectory in AI image synthesis.

Defense mechanism for multi-agent systems against infectious jailbreak attacks via foresight-guided local recovery.

User documents Claude Code CLI behavior on Windows 11 with Opus 4.7 when system dependencies are missing.

Online causal framework for auto-bidding in second-price auctions models marginal value vs. realized revenue.

Linear dueling bandits algorithm handles delayed feedback, adversarial corruption, and post-serving context simultaneously.

Iterated negotiation benchmark tests LLM agents' ability to repair grounding failures in dynamic multi-turn interaction.

Decoupled exploration-commitment paradigm reduces hallucinations in long-form reasoning by fine-grained control over information selection across reasoning steps.

NH-CROP framework prices language data assets under cost uncertainty with information-acquisition gates for NLP tasks.

OpenClaw agentic-AI runtime fails to catch four critical safety failures (gate-bypass, audit-forgery, host failure, wrong-target) in production deployment.

Geometric unlearning method removes specific content from LLMs without full training corpus access, balancing privacy and model utility.

GEASS steering mitigates object hallucination in vision-language models by asymmetric caption weighting without retraining.

EGAD entropy-guided knowledge distillation improves token-level transfer by weighting per-token importance in student model training.

GFlowNet training stability improved via loss-to-TV bounds that provide probabilistic guarantees against mode collapse.

LLMs exhibit genre-dependent credibility assessment bias, misclassifying entertainment news as fake more often than hard news.

FEDIN captures latent periodic patterns in user behavior for click-through prediction via frequency-domain spectral entropy analysis.

Motion-aware caching accelerates autoregressive video generation by adaptive denoising step allocation based on pixel motion density.

SignVerse-2M dataset adds 2M pose-annotated sign language clips across 25+ languages for improved recognition and generation.

TCDA improves conversational sentiment analysis by modeling dialogue threads with positional awareness instead of flat sequences.

CoAction framework enables single multi-task Pareto set learning model instead of separate models per task.

Route receipts propose audit trails for model routing decisions in adaptive AI systems to ensure transparency and accountability.

SplitZip achieves ultra-fast KV cache compression for disaggregated LLM serving, addressing bottleneck in prefill-decode architecture.

Federated learning framework for 5G jamming detection preserves privacy vs. centralized approaches.

Reasoning Trap formalizes why multi-agent debate preserves answer accuracy but degrades reasoning via information-theoretic bounds.

Floating-point networks under automatic differentiation can approximate differentiable functions and gradients despite finite precision.