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DR-MPC: Fast and Feasible Dynamics-Relaxed Model-Predictive Control for Legged Locomotion

arXiv:2609.20035v1 Announce Type: new Abstract: This paper presents dynamics-relaxed model predictive control (DR-MPC), a novel MPC formulation for legged locomotion, and a tailored interior-point met

researcharxiv-cs-ro

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Drag-Aware Aerodynamic Manipulability for Torque-Limited Redundant Multirotors: Aerodynamic Promptness based on the Symmetric Acceleration Capacity

DGX agent

arXiv:2603.07998v2 Announce Type: replace-cross Abstract: Aerodynamic promptness quantifies how rotor-speed variations generate multirotor wrench variations, but its Euclidean formulation assigns the

model-releasesarxiv-cs-ai

18 Sept 2026

dual 7900 xtx - some guy made a pretty optimized fork of lamacpp optimized for this setup Qwen 3.8 Q8 at 82 tokens / seconds decode

model-releasesr-localllama

Note not my work, but something i found and wanted to share so hopefully more people can push this along even further. https://github.com/nasone32/llama.cpp-RDNA3-7900xtx-opt I basically run 2 x 7900

Dual-Axis Policy Optimization for LLM Agents: Bayesian Feedback Attribution and Trajectory Mass Normalization

arXiv:2609.19830v1 Announce Type: new Abstract: Reinforcement learning for LLM agents involves two distinct optimization di- mensions: how environment feedback is exploited within a trajectory, and ho

safetyarxiv-cs-ai

Dynamic Generalized Gromov-Wasserstein Optimal Transport

arXiv:2609.20008v1 Announce Type: cross Abstract: Gromov--Wasserstein optimal transport (GW-OT) extends classical optimal transport by introducing structure-aware transport cost. This is particularly

safetyarxiv-cs-ai

Dynamic-LIVO: A Dynamic-Aware LiDAR-Inertial-Visual Odometry System Using Spatio-Temporal Normals

model-releasesarxiv-cs-ro

arXiv:2609.19336v1 Announce Type: new Abstract: This paper proposes Dynamic-LIVO, a dynamic-aware LiDAR-Inertial-Visual Odometry (LIVO) system for robust state estimation and static colored mapping in

DynaWeightPnP: Toward global real-time 3D-2D solver in PnP without correspondences

arXiv:2409.18457v2 Announce Type: replace Abstract: This paper addresses a special Perspective-n-Point (PnP) problem: estimating the optimal pose to align 3D and 2D shapes in real-time without corresp

safetyarxiv-cs-cv

E-AVI: Evidence-Grounded Multimodal Assessment for Automated Video Interviews

arXiv:2609.20001v1 Announce Type: new Abstract: Automated video interview assessment integrates verbal content, acoustic delivery, and visual behavior, yet numerical predictions alone provide limited

Local Ai

Earth Surface Immune System for Rapid Monitoring of Unknown Anomalies

arXiv:2609.20662v1 Announce Type: new Abstract: Earth surface anomalies, driven by escalating climate change, and expanding human activities, are increasing in both frequency and diversity, yet their

local-aiarxiv-cs-cv

Agents

EconSkills: Studying Skill Transfer and Retrieval for Web Agents on Live Economic Data

arXiv:2609.19523v1 Announce Type: new Abstract: Web agents often revisit the same sites, yet most evaluations discard the procedures learned in earlier successful interactions. We introduce EconSkills

agentsarxiv-cs-ai

Edustories: A Collection of Real-world Case Studies from Classroom Practices

arXiv:2609.20484v1 Announce Type: cross Abstract: Despite the widely recognized potential of AI in education, most prior work has focused on individualized student assistance. In contrast, the majorit

applicationsarxiv-cs-ai

Effective and Efficient Threat Hunting with Small Language Models

arXiv:2512.06660v3 Announce Type: replace-cross Abstract: Analysts in Security Operations Centers query massive telemetry streams using Kusto Query Language (KQL), but writing correct KQL demands spec

Efficient Nash Equilibrium Computation for Cybersecurity Games

arXiv:2609.19399v1 Announce Type: cross Abstract: Computing Nash equilibria of simulation-based cybersecurity games with policy-space response oracles (PSRO) is bottlenecked by payoff estimation: ever

safetyarxiv-cs-ai

Efficient Unified Multimodal Understanding (EUMU): Winning Solution for the MUMU Track at the 8th LSVOS Challenge

arXiv:2609.19451v1 Announce Type: new Abstract: The Mobile Unified Multimodal Understanding (MUMU) Challenge requires a single efficient model to jointly perform multi-concept image tagging, open-voca

researcharxiv-cs-cv

Efficiently Distributed Federated Learning

arXiv:2609.19972v1 Announce Type: cross Abstract: Federated Learning (FL) is experiencing a substantial research interest, with many frameworks being developed to allow practitioners to build federati

Agents

Efficiently Linking Unstructured Data for Multi-step Reasoning

arXiv:2609.19491v1 Announce Type: cross Abstract: Modern LLMs and AI agents increasingly support data engineering workflows that integrate evidence from unstructured sources. Such pipelines typically

agentsarxiv-cs-ai

Elastic Spectral State Space Models for Train-Once Budgeted Inference

arXiv:2601.22488v3 Announce Type: replace Abstract: Modern sequence models are typically trained at a fixed computational capacity, while real-world applications require deployment across platforms wi

EliGSiR: Continual RGB-D Mapping with Gaussian Splatting under Bounded Compute

arXiv:2609.20348v1 Announce Type: new Abstract: Conventional 3D Gaussian Splatting assumes a closed set of observations and long optimization schedules. Continual RGB-D mapping in contrast poses the p

researcharxiv-cs-cv

Embedding Models Measure in Peculiar Ways

arXiv:2609.20821v1 Announce Type: new Abstract: Embedding spaces define notions of semantic similarity and distance. We study whether those embeddings reflect physical measurements of mass, distance,

safetyarxiv-cs-cl

EmbodiedMind: Adaptive Data Curation and Prefix-Tree Reinforcement Learning for Efficient Embodied Intelligence

arXiv:2609.19659v1 Announce Type: cross Abstract: Training embodied foundation models typically requires massive-scale datasets and extensive computational resources, yet often suffers from three crit

Emergent interactions lead to collective frustration in robotic matter

arXiv:2507.22148v3 Announce Type: replace-cross Abstract: Artificial intelligence and robotic systems are increasingly deployed as interacting collectives of learning agents. This raises the question

researcharxiv-cs-ro

Enabling automatic transcription of child-centered audio recordings from real-world environments

arXiv:2506.11747v2 Announce Type: replace-cross Abstract: Longform audio recordings obtained with microphones worn by children-also known as child-centered daylong recordings-have become a standard me

applicationsarxiv-cs-lg

Engrams Embedding Entendre: Codesign for Efficient DRAM/SSD Offloading

model-releasessemianalysis

Engram Embedding Entendre is a model‑architecture optimization that extends standard token embeddings with learned multi‑token lookups, enabling recurring local patterns to be retrieved directly from

Enhanced Agriculture-informed Neural Network by Domain Knowledge

arXiv:2609.19466v1 Announce Type: new Abstract: Accurate prediction of nitrous oxide (N2O) emissions from agriculture is important for assessing environmental impacts and supporting sustainable farmin

Enhanced Knowledge Distillation for Detection Transformer via Teacher Prediction Refinement

arXiv:2609.19964v1 Announce Type: new Abstract: Detection Transformers (DETRs) achieve strong performance in object detection but remain challenging to deploy on edge devices due to their high computa

applicationsarxiv-cs-cv

Enhancing the Perception of Safety and Comfort during Physical Human-Robot Handshake Interactions by Integrating Flexible Elements into a Robotic Arm

arXiv:2609.19375v1 Announce Type: new Abstract: Safety and comfort in human-robot physical in-teractions are essential aspects in the development of social technologies, where natural gestures, such a

safetyarxiv-cs-ro

Epidemiological Causal Graph Identification: Challenges, Identifiability and Algorithms

arXiv:2609.20676v1 Announce Type: new Abstract: Causal discovery from observational data is fundamental to statistics and machine learning, yet determining causal direction without interventions neces

Local Ai

EPIG-Tree: Compute-Optimal Branching for Gradient-Efficient Reinforcement Learning

arXiv:2609.20004v1 Announce Type: cross Abstract: Reward-based reinforcement learning for language models, exemplified by Group Relative Policy Optimization (GRPO), collapses an entire stochastic traj

local-aiarxiv-cs-ai

Epoch continues to do some of the best public benchmarking work on AI. This is helpful (and tells us how bad the state of benchmarking is, a…

model-releasesethan-mollick--x

Epoch continues to do some of the best public benchmarking work on AI. This is helpful (and tells us how bad the state of benchmarking is, and how terrible some of our favorite benchmarks are) Introdu

Equivariant Filter Design for Acoustic and Depth Aided Inertial Navigation Systems

model-releasesarxiv-cs-ro

arXiv:2609.19742v1 Announce Type: new Abstract: Autonomous Underwater Vehicles (AUVs) navigating without GPS typically fuse inertial measurements with acoustic Doppler Velocity Log (DVL) velocities an

ERCPMP-Gx: Endoscopic Image and Video Dataset for Morphological, Histopathological, and Genomic Characterization of Colorectal Polyposis

arXiv:2609.20815v1 Announce Type: cross Abstract: Hereditary polyposis syndromes can be precursor lesions to colorectal cancer and are associated with a broad spectrum of extracolonic tumors. Early id

Error bounds in Sobolev norms for approximations with norm constrained ReLU neural networks

arXiv:2609.19937v1 Announce Type: cross Abstract: Recent studies have shown that smooth functions can be well approximated by ReLU neural networks with path norm constraint on the weights. We extend t

Estimation of multiple mean vectors in high dimension

arXiv:2403.15038v3 Announce Type: replace-cross Abstract: We endeavour to estimate numerous multi-dimensional means of various probability distributions on a common space based on independent samples.

applicationsarxiv-cs-lg

Evaluating Communicative Success in Machine-Translated Conversation

model-releasesarxiv-cs-cl

arXiv:2609.19885v1 Announce Type: new Abstract: Interpreter agents built on machine translation (MT) increasingly mediate live conversation between people who do not share a language, yet we still eva

Local Ai

Evaluating Explanation Methods by the Predictors They Induce

arXiv:2609.20058v1 Announce Type: new Abstract: Explanations of machine learning models are usually judged by criteria that are hard to compare. We propose a simpler test: if an explanation really des

local-aiarxiv-cs-lg

Evaluating Financial Sentiment in the Age of AI

arXiv:2609.20198v1 Announce Type: new Abstract: Financial sentiment measures are widely used in empirical finance, but it remains unclear whether general-purpose large language models (LLMs) improve o

applicationsarxiv-cs-lg

Evaluating Out-of-Distribution Robustness in Graph-Based Android Malware Classification: A New Principled Benchmark

arXiv:2508.06734v3 Announce Type: replace-cross Abstract: While graph-based Android malware classifiers report strong benchmark accuracy of over 94%, their performance sharply decreases up to 45% when

even the anti-woke media sure loves this narrative. doesn’t make it true.

even the anti-woke media sure loves this narrative. doesn’t make it true. 'I worked at OpenAI for two years before resigning in 2024. Fears that AI will cause human extinction are real. You should tak

safetygary-marcus--x

EviRec: Continual Evidence Learning for Dual Cold-Start POI Recommendation

arXiv:2609.20313v1 Announce Type: new Abstract: Point-of-Interest (POI) recommendation is a core task in location-based services, yet most existing methods assume a fixed user population and POI catal

Evolution or Illusion? Rethinking Evaluation in LLM Evolutionary Search

arXiv:2609.19799v1 Announce Type: cross Abstract: LLM-driven evolutionary search finds programs by launching seeds and iterating each one. Papers report a single budget setting, usually one seed run f

Execution-Aware Pre-Execution Ranking for Grasp-Conditioned Robotic Placement

arXiv:2609.19946v1 Announce Type: new Abstract: A geometrically valid placement can still be difficult to execute because the selected grasp changes the required end-effector pose, collision geometry,

researcharxiv-cs-ro

Expected Hypervolume Maximization for Multiobjective Optimization under Uncertainties

arXiv:2609.19858v1 Announce Type: new Abstract: The problem of multiobjective optimization under uncertainties is often approached by taking the expectation of each objective. In this work, we propose

Explaining spatial information flow in short-term traffic forecasting models using a gated graph attention network

arXiv:2609.20217v1 Announce Type: new Abstract: Short-term traffic forecasting supports real-time monitoring and control of road networks, and graph attention networks (GAT) are the standard means of

Exploring a Layer-Wise Design Space for KV Cache Eviction

arXiv:2606.15157v2 Announce Type: replace-cross Abstract: KV cache eviction methods typically use a single retention-rule family throughout a model, making eviction-method identity a model-level desig

Exploring Sparsity and Smoothness of Arbitrary Lp Norms in Adversarial Attacks

arXiv:2602.06578v2 Announce Type: replace-cross Abstract: Adversarial attacks against deep neural networks are commonly constructed under ell_p norm constraints, most often using p=1, p=2 or p=infty,

F^{2}DR: A Fine-Grained Full-Pipeline Reward Framework for DeepSearch Workflows

model-releasesarxiv-cs-cl

arXiv:2609.19827v1 Announce Type: new Abstract: With the widespread industrial deployment of Large Language Models (LLMs), DeepSearch has emerged as the dominant paradigm for resolving complex user qu

FacetCRS: Multi-Faceted Preference Learning for Pricking Filter Bubbles in Conversational Recommender System

arXiv:2609.20175v1 Announce Type: cross Abstract: The filter bubble is a notorious issue in Recommender Systems (RSs), which describes the phenomenon whereby users are exposed to a limited and narrow

Agents

Factors Influencing the Emergence of Dependency Length Minimization in Neural Agent Simulations

arXiv:2609.06025v2 Announce Type: replace Abstract: Given various grammatical options, language users prefer the word order choice that reduces the overall length of syntactic dependencies, a principl

agentsarxiv-cs-cl