Search: “papers”

FlashAttention for Scalable Vector Architectures

arXiv:2608.18656v1 Announce Type: new Abstract: Inference with transformer models on CPUs is increasingly important, especially for Small Language Models (SLMs), where vector architectures are emergin

Forgetting, plasticity, and co-observation: a third facet of continual learning

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DGX agent

arXiv:2608.18803v1 Announce Type: cross Abstract: Efficient continual learning remains a fundamental challenge for deep neural networks. While catastrophic forgetting and loss of plasticity are widely

researcharxiv-cs-ai

20 Aug 2026

Generalized Audio-Driven Synthesis of Precise Drummer Motion

arXiv:2608.19055v1 Announce Type: new Abstract: Music-driven character animation enables and enhances transformative applications in entertainment and interactive education. However, synthesizing real

safetyarxiv-cs-cv

Grading the Graders: Verification Autonomy Levels (L0-L5) for LLM Reasoning

arXiv:2608.19009v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly paired with verifiers (step checkers, self-consistency filters, tool-based fact checkers, formal proof ass

Hallucination Detection in Large Language Models Using Diversion Decoding

arXiv:2607.10476v2 Announce Type: replace Abstract: Large language models (LLMs) have emerged as a powerful tool for retrieving knowledge through seamless, human-like interactions. Despite their advan

researcharxiv-cs-cl

HarvestPoint-ACT: Explicit Target Selection and Harvest-Point Conditioning for Robotic Fruit Harvesting under Occlusion

arXiv:2608.18446v1 Announce Type: new Abstract: End-to-end imitation learning avoids hand-made robot motion for approaching and grasping, but the policy must still decide which fruit to pick and where

safetyarxiv-cs-ro

LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum

arXiv:2601.01684v2 Announce Type: replace-cross Abstract: While dense retrieval models have been the standard for state-of-the-art information retrieval, their deployment is often constrained by high

Tutorials

Learning Topological Features of widehat Z-invariants

arXiv:2608.18570v1 Announce Type: cross Abstract: Machine learning and data analysis techniques have recently emerged as powerful tools for identifying patterns and formulating conjectures in mathemat

tutorialsarxiv-cs-lg

LongNovel: A Multi-Scale Benchmark for Hallucination Detection in Long-Context Novel Summarization

arXiv:2608.18082v1 Announce Type: new Abstract: Although context windows have expanded significantly in recent years, hallucinations in long-context summarization remain a challenge. Long novels are b

Local Ai

Mitigating Spectral Bias in Neural Operators for Underwater Transmission Loss Prediction

arXiv:2608.18141v1 Announce Type: cross Abstract: Predicting underwater acoustic transmission loss rapidly and accurately is crucial for real-time ocean acoustic applications. While Fourier Neural Ope

local-aiarxiv-cs-lg

Monroe: A Molecular Foundation Model for In-Context Probabilistic Inference

arXiv:2608.18982v1 Announce Type: new Abstract: Bioassay activity prediction is often data-limited because drug-discovery datasets rely on time-consuming and expensive wet-lab experiments for data gen

researcharxiv-cs-lg

Multi-Agent Off-Policy Deep Reinforcement Learning for Smart Campus Coverage

arXiv:2608.19049v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) has recently gained a great attention due to its real-time adaptation and effectiveness in complex optimization proble

On the Power of Source Screening for Learning Shared Feature Extractors

arXiv:2602.16125v3 Announce Type: replace Abstract: Learning with shared representation is widely recognized as an effective way to separate commonalities from heterogeneity across various heterogeneo

applicationsarxiv-cs-lg

One Gate Is Not Enough: Composing Stateful Pre-Action Controls for Agentic AI

arXiv:2608.18360v1 Announce Type: cross Abstract: Agentic AI systems take consequential actions governed by more than one pre-action control at once: authority, resource, and evidence gates that can a

Local Ai

Optic Disc Segmentation in Fundus Images: From Classical Image Processing and Deformable Models to Modern AI

arXiv:2608.18367v1 Announce Type: cross Abstract: Accurate localization and segmentation of the optic disc (OD) are important for retinal image analysis and glaucoma assessment, yet remain challenging

local-aiarxiv-cs-cv

PCQA-R1: Advancing Generalized 3D Point Cloud Quality Assessment with Reinforcement Learning

arXiv:2608.18627v1 Announce Type: new Abstract: No-reference point cloud quality assessment (PCQA) has been an active topic in recent years and is used to measure and optimize the visual experience of

safetyarxiv-cs-cv

Position: Behavioral Systems Require Behavioral Tests

arXiv:2608.18081v1 Announce Type: new Abstract: Artificial agentic systems increasingly operate as behavioral systems by interacting with dynamic environments, pursuing goals, and adapting over time.

Position: Current Model Cards Are Insufficient for Downstream Governance of Open-Weight Foundation Models

arXiv:2608.18086v1 Announce Type: new Abstract: The growth of open-weight foundation models (OWFMs) has prompted the AI community to re-evaluate strategies for effective downstream governance. Althoug

safetyarxiv-cs-ai

Professional Software Developers Don't Vibe, They Control: AI Agent Use for Coding in 2025

arXiv:2512.14012v2 Announce Type: replace-cross Abstract: The rise of AI agents is transforming how software can be built. The promise of agents is that developers might write code quicker, delegate m

Revisiting the 'Push-T' Robot Manipulation Task with Agentic Robotics

model-releasesarxiv-cs-ro

arXiv:2608.18227v1 Announce Type: new Abstract: Push-T is an iconic benchmark for learning manipulation policies from human demonstrations. The robot must use a single point of contact to push a T-sha

Self-Improvement of Large Language Models: A Technical Overview and Future Outlook

arXiv:2603.25681v2 Announce Type: replace Abstract: As large language models (LLMs) continue to advance, improving them solely through human supervision is becoming increasingly costly and limited in

agentsarxiv-cs-cl

SkillForge: Self-Distilling Agents for Project-Specific Issue Resolution

arXiv:2608.18933v1 Announce Type: cross Abstract: Large language model (LLM) based agents have demonstrated remarkable proficiency in automated software issue resolution, yet they often struggle to re

Hardware

SMTrap: Cost-Effective DoS Attacks Against Large Reasoning Models via SMT Conflict Guidance

arXiv:2608.18921v1 Announce Type: cross Abstract: Existing LRM-DoS methods rely heavily on model feedback to synthesize attack queries, requiring either repeated queries to the target model or trainin

hardwarearxiv-cs-ai

Structure-Informed Estimation for Pilot-Limited MIMO Channels via Tensor Decomposition

arXiv:2602.04083v3 Announce Type: replace-cross Abstract: Accurate channel state information in wideband MIMO systems is constrained by pilot overhead, a challenge intensifying as bandwidths scale tow

Syntactic Simplification of OWL Class Expressions

arXiv:2608.18899v1 Announce Type: new Abstract: Class expression learning often produces complex OWL class expressions that are difficult to interpret and reason over. However, by following theoretica

Temporal Multi-Signal Fusion for Token-Level Hallucination Detection

arXiv:2608.18115v1 Announce Type: cross Abstract: Token-level hallucination detectors score each token independently from a single signal, and fail exactly when the generating model is confidently wro

The spectral neuron - an ML primitive for scalable and interpretable models [R]

researchr-machinelearning

Worked some time ago on one of the ad teams at Yahoo, and this grew out of a question I kept returning to while there are there 'simple' models that are both simple, scalable, interpretable, and contr

Trust as a Field: A Macroscopic Representation for Vehicular Networks

arXiv:2608.18178v1 Announce Type: new Abstract: Trust assessment is a fundamental component of cooperative and connected vehicle systems. However, existing approaches operate primarily at the level of

researcharxiv-cs-ro

UMER: Unifying Embedding and Ranking via Pair-Aware Discriminative Reasoning for Universal Multimodal Retrieval

model-releasesarxiv-cs-ai

arXiv:2608.18504v1 Announce Type: new Abstract: Universal multimodal retrieval aims to support diverse instruction-aware retrieval tasks, demanding both efficient corpus-scale matching and fine-graine

Understanding Multilingual Medical ASR Adaptation Through Layer-Wise Analysis

arXiv:2608.18825v1 Announce Type: cross Abstract: Medical automatic speech recognition (MedASR) requires adaptation to specialised terminology, limited annotated clinical data, and multilingual use ca

Visual-Aware Representation of Web Pages for Machine Learning Applications

arXiv:2608.18727v1 Announce Type: new Abstract: Applying machine learning to web pages is challenging due to the need to interpret HTML together with associated resources and perform rendering to obta

researcharxiv-cs-lg

VTONQA: A Multi-Dimensional Quality Assessment Dataset for Virtual Try-on

model-releasesarxiv-cs-cv

arXiv:2601.02945v2 Announce Type: replace Abstract: With the rapid development of e-commerce and digital fashion, image-based virtual try-on (VTON) has attracted increasing attention. However, existin

Zero-Shot Transfer of Force Map Estimation Across GelSight Mini Sensors

arXiv:2608.18240v1 Announce Type: new Abstract: Despite the rapid industrialization of the touch sensor manufacturing process, most of these sensors are still handmade in research laboratories. This c

applicationsarxiv-cs-cv

A decodability criterion predicts when hidden-state selection beats majority voting in large language models

arXiv:2608.17124v1 Announce Type: new Abstract: Combining the answers a large language model (LLM) samples for a question into one decision is a test-time information fusion problem, usually solved by

A Diffusion-Refined Planner with Reinforcement Learning Priors for Confined-Space Parking

arXiv:2510.14000v2 Announce Type: replace Abstract: The growing demand for parking has increased the need for automated parking planning methods that can operate reliably in confined spaces. In restri

safetyarxiv-cs-ro

A Theoretical Framework for Parallel Lifelong MAPF Using Group Decentralized Planning

arXiv:2608.17928v1 Announce Type: cross Abstract: In the Lifelong Multi-Agent Path Finding (L-MAPF) problem, agents must repeatedly move from one destination to another while avoiding obstacles and in

Accuracy and Robustness of Model Cascades Under Data Perturbations

arXiv:2608.17711v1 Announce Type: new Abstract: Prediction cascades significantly reduce energy consumption of Artificial Intelligence (AI) models while maintaining high predictive performance. The id

aDSL: Agentic 3D Creation via Joint Agent-Program Design

arXiv:2608.17975v1 Announce Type: cross Abstract: Programmatic representations provide a compelling paradigm for 3D content creation, enabling fine-grained edits, interpretability, and explicit struct

agentsarxiv-cs-cv

Agentic ESOpt: Fine-Tuning Long-Horizon LLM Agents with Minimal GPU Requirements

arXiv:2608.17310v1 Announce Type: new Abstract: Reinforcement Learning (RL) has been promising in single-turn LLM fine-tuning. However, long-horizon agentic reasoning introduces increasingly branching

Analysis of Types of Inquiries in Student-AI Interaction: A case study of two CS2 tasks

arXiv:2608.17919v1 Announce Type: cross Abstract: Background and Context: Question and inquiry are integral parts of knowledge seeking and learning. Despite their importance, students tend not to ask

applicationsarxiv-cs-ai

ARASH: Adaptive Retrieval And Shot Selection for Tabular Prediction

arXiv:2608.17856v1 Announce Type: new Abstract: Tabular prediction is a critical task across numerous applications. The recent success of large language models has sparked various approaches for adapt

Backward through Time, Algebraically

arXiv:2608.17087v1 Announce Type: new Abstract: Linear temporal logic is a modal extension of propositional logic that allows one to state how a system should behave over time. Its canonical domain is

researcharxiv-cs-lg

Benchmarking Classical and Transformer-Based Models for Document Sensitivity Classification

arXiv:2608.16928v1 Announce Type: new Abstract: Automatic sensitivity classification of organizational documents is a critical yet underserved problem, where the consequences of misclassification rang

Hardware

Beyond FLOPs: Energy-Aware Knowledge Distillation for Sustainable LLMs on Code-Related Task

arXiv:2608.17515v1 Announce Type: cross Abstract: Background: Large Language Models (LLMs) are increasingly being applied to Software Engineering (SE) tasks, achieving high accuracy across problems su

hardwarearxiv-cs-ai

Calibrated Predictive Safety for Heterogeneous Robots: An Action-Conditioned JEPA Framework with Model-Based Safety Shields

arXiv:2608.17496v1 Announce Type: new Abstract: Vision-language-action policies generalize broadly but provide no execution-time guarantees; classical model-based planners respect kinematic and geomet

safetyarxiv-cs-ro

Chain-of-Experience for Continual LLM Improvement

arXiv:2608.18027v1 Announce Type: new Abstract: Humans continuously learn from experience, whereas conventional large language model (LLM) evaluations ignore the models' ability to improve through inf

ChatPlanner: A Large Language Model Framework for Personalized Public Transit Routing

arXiv:2606.15315v2 Announce Type: replace Abstract: Personalized public transit routing in public transit systems remains challenging due to the difficulty of capturing and integrating diverse user pr

CoAL-RAG: A Complexity-Aware Legal Retrieval-Augmented Generation Method

arXiv:2608.17536v1 Announce Type: cross Abstract: Legal consultation questions exhibit multi-level complexity. A single retrieval strategy often leads to over-reasoning for simple questions and poor i

applicationsarxiv-cs-ai