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More and more of your terminal work now runs through tools that push the terminal harder than a shell prompt ever did: AI coding agents like Claude Code and Codex, full-screen apps like Neovim and tmux, system monitors and dashboards. These tools lean on modern terminal protocols, the kind today’s best standalone terminals are built […]
Extends secure aggregation for federated learning to heterogeneous client quantization without projecting to common finite groups.
Federated learning analysis of SCAFFOLD algorithm convergence under Hessian similarity for heterogeneous data.
SimPOTrans adapts offline speech translation to simultaneous settings via RL, enabling low-latency translation without synthesized training trajectories.
U-NeXt: semantic segmentation framework for neonatal EEG event detection across 51–278 neonates and 11,000+ hours of recordings.
Ariadne transfers task-specific fine-tuning behavior across differently-sized Transformers without parameter resizing, enabling efficient model adaptation across architectures.
PYTHIA framework applies transfer learning and foundation models to material defect and adsorption site optimization with reduced sample requirements.
PhyNet framework for industrial fault diagnosis treats physical variables as global constraints and response signals as diagnostic evidence in heterogeneous sensor streams.
LatBridge enables safe model replacement in multi-agent systems by bridging latent-communication interfaces across heterogeneous agent architectures.
WeAct enables long-horizon agents to avoid catastrophic forgetting by treating adapter selection as learned actions, managing heterogeneous capabilities.
Monsoon framework collects spontaneous-speech ASR data across 50 languages with multi-stage quality control, reducing WER.
Doubly robust learning method estimates heterogeneous survival treatment effects under time-varying treatments with sequential censoring adjustment.
REP-HO replaces manual heuristics in mixed-fidelity optimization with LLM-based evaluation planning for heterogeneous multi-objective problems.
PRISMA algorithm evaluates K policies simultaneously in contextual bandits with sample complexity scaling in log(K).
FutureLift refines multimodal motion forecasts by representing proposals as heterogeneous future graphs for autonomous driving.
Lightweight HTTP/SSE-based Agent Status Protocol for heterogeneous multi-agent systems to report operational state and infer liveness via heartbeats.
Retraining-free elastic scaling of transformers enables single model to adapt across heterogeneous computational budgets via differentiable unit-ranking.
Analysis of simple relational baselines versus GNNs and Transformers for temporal heterogeneous graph prediction over relational databases.
Asynchronous multi-player multi-armed bandits with heterogeneous activation probabilities: theoretical analysis of optimal decentralized allocation.
CloneOT uses lineage-supervised neural optimal transport to predict single-cell perturbation responses by learning transport costs from heritable barcodes.
HACE framework enables self-improving LLM agents and specialized foundation models to coevolve, where improvement strategies adapt as domain-specific models advance.
Orthros attention dynamically switches computation patterns across sequence processing phases to maintain in-context recall while reducing quadratic complexity bottleneck.
PRISM multimodal LM for clinical prognosis integrates structured measurements, ECG waveforms, and population-retrieved embeddings via dual-modality memory.
FedPCD proposes priority-constrained federated optimization to improve fairness across heterogeneous clients without symmetric weighting.
The NVIDIA KGMON team placed second in the KDD Cup 2026 Data Agents competition with a system built around a simple idea of making an agent's harness smaller,... The NVIDIA KGMON team placed second in the KDD Cup 2026 Data Agents competition with a system built around a simple idea of making an agent’s harness smaller, clearer, and easier to verify. The competition asked agents to answer natural-language questions over heterogeneous data sources, including databases, CSV and JSON files, prose documents, PDFs, and briefing videos. Source
UXBench Pro introduces 1,000 multi-turn dialogue instances with personalized user profiles for evaluating heterogeneous user preferences beyond binary reward models.
Personalized federated linear stochastic approximation with adaptive convergence and speedup guarantees for heterogeneous agent learning.
Conditional Flow Matching for generative urban microclimate prediction: replaces deterministic LES surrogates with probabilistic 3D wind/temperature field synthesis.
Multi-agent reinforcement learning scheduler for time-sensitive vehicular edge computing networks with heterogeneous latency requirements.
Wander is a graph foundation model using random walks as a unified interface to transfer across heterogeneous graphs, features, and tasks.