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Agents

Hybrid Reasoning Agents

DGX agent

arXiv:2610.18861v1 Announce Type: cross Abstract: How can we build an agent that thinks beyond human language, yet still acts through it in the external environment? Modern LLM agents still reason and

agentsarxiv-cs-lg

14 Oct 2026

Agents

I really don’t understand the point of the AI slopcomments flooding my posts. At least on LinkedIn they are pushing fake expertise to make t…

DGX agent

Search: “models”

Hybrid Reasoning Agents

I really don’t understand the point of the AI slopcomments flooding my posts. At least on LinkedIn they are pushing fake expertise to make t…

In View or Out of View? A Vision-Aware Filter that Infers and Reacts to the Human's Field of View

Insightful paper on recursive self-improvement with a frozen LLM. (bookmark it) Memento 3 clears every level of all 25 public ARC-AGI-3 game…

Interaction-as-a-Judge

Intrinsic Geometry Matching: learning observation-equivariant process geometry

Introducing the largest open-source multilingual, multimodal RL environments 🌍 📄 OCR: 1M+ document pages in 22 languages 🎙️ ASR: speech i…

Is the Platform Part of the Measurement? A Protocol and Simulation Study for Cross-Platform Equivalence of Machine-Labelled Policy Sentiment

Jacobian State Augmented Viable Kinematic Safety Filter

Joint Embedding with Dynamic Integration network (JEDI-net)

JSIR: An Audio-Aligned, Multi-Task Dataset of Jazz Standard Recordings

Just Respect the Semantics: Image-Token Compression via Pre-LLM Semantic Variable-Resolution Tokenization and In-LLM Relevance Pruning

KedgeFlow: A Programmable Control Plane for Enterprise AI Agents

Last-Iterate Convergence of Clipped SGD with Linear Decay

Latent-Space Importance Weighting under Covariate Shift

Layer-wise Input Recoverability in Deep Neural Networks

Learning Deployable Causal Action Geometry under Temporal Non-Stationarity

Learning Dynamic Grasping

Learning Incompressible 3D Flows from Sparse Samples: A Set Transformer Approach to Divergence-Free Kernel Fitting

Learning Source Structure: Bayesian Prediction with Transformers

Learning to Sync at the Edge: Client-Side Adaptive Synchronization for Federated Learning

LETS: Low-Overhead External-Torque Sensing for Force-Feedback Bilateral Teleoperation

LexiCan: Lexicographic Canonicalization of Point Clouds for Machine Learning Applications

LLM-Augmented Bayesian Optimization with Adaptive Policies for Chiplet Design Space Exploration

LLM-HB: Language-Aware LLM-Guided Hotword Biasing for Code-Switching ASR

LLM Judges Have Dark Current: Stratified Null and Utility Tests for LLM Judge Reliability

LLM-to-Flow Distillation: Teaching Natural Language Goals to Scientific Generators

Look Before You Move: Agent-Interface-Aligned Supervision for Open-World Mobile Manipulation

Looped Reasoning Finishes Earlier Than You Think

Make {pi}0.5 Learn to Call Astra for Reliable Robot Manipulation

MARTS: A Modular Agricultural Robot for Targeted Spraying of Diseased Tomato Plants in Greenhouses

Meaningful Moments: A Corpus of VLM-Derived Temporal Importance Labels for Video Action Recognition

Memory Without Curation: Learning Multi-Stream Latent Memory for Robot Policies

MENTOR: Procedural Shielding of Tool-Using LLM Agents

Metadata-Guided Adaptable Frequency Scaling across Heterogeneous Applications and Devices

Mining Cross-Modal Perception Gaps in Autonomous Driving: When Camera and LiDAR Disagree

MIST: Multi-Scale Spatial Context for Gene Expression Prediction from Histology

MoSAIC: Learning DAG Scheduling Heuristics from Optimal Schedules through Motif-Aware Recovery and LLM-Guided Reasoning

MvFFN: Multi-view Floor plan Feed-forward Network for Unposed Wide-Baseline Panorama Layout Reconstruction

NetRL: Powering Network Decisions via NetGRPO-Driven Reinforcement Learning

NeuSE: Neural SE(3)-Equivariant Embedding for Long-Term Object-Based Simultaneous Localization and Mapping

OctMole: Multiscale 3D Molecular Generation with Hierarchical Spatial Flows

OIL: An Object Interaction Layer for Humanoid Whole-Body Control

On Making SE(2)-Invariant Networks Optimal

On physical implementability of reinforcement-learning-driven reasoning

On the Theoretical Limits of Learning Unconstrained Interatomic Potentials

One-Layer Transformers Provably Learn In-Context K-Nearest Neighbor Prediction with Chain-of-Thought

Optimizing Team Behavior via Extremum-seeking Control in Multi-agent Reinforcement Learning