Search: “models”

arXiv:2608.27271v1 Announce Type: cross Abstract: The marine science community increasingly relies on Marine Autonomous Vehicles (MAVs) to collect the critical environmental data required to understan

agentsarxiv-cs-ro

Multi-Person Human Motion Forecasting in Complex Scenes

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DGX agent

arXiv:2608.27039v1 Announce Type: cross Abstract: Accurately forecasting the movement of people in complex scenes requires reasoning over the past and present state of the entire environment. In this

researcharxiv-cs-ai

28 Aug 2026

Muon with Finite Newton-Schulz: The Smoothing Benefit in Nonsmooth Nonconvex Optimization

arXiv:2608.26288v1 Announce Type: new Abstract: Muon has emerged as a strong optimizer for the matrix-valued parameters in large language model pretraining, approximately orthogonalizing its momentum

NEvo: Neural-Guided Evolutionary Video Synthesis for Dynamic Visual Selectivity

arXiv:2607.02317v2 Announce Type: replace Abstract: The human brain processes dynamic visual input through hierarchically organized, functionally specialized regions. While recent in silico brain enco

Not All Eval-Awareness Is Equal: Capabilities Framing Predicts Compliance

arXiv:2608.27340v1 Announce Type: new Abstract: Steering interventions targeting eval-awareness, a model's recognition that it is being tested, are increasingly used in safety evaluation pipelines, wh

safetyarxiv-cs-ai

Agents

Obligatory plug for static embeddings. Are you using static embeddings in your projects? Would love to hear how people are leveraging them, …

Obligatory plug for static embeddings. Are you using static embeddings in your projects? Would love to hear how people are leveraging them, whether for retrieval and beyond. Static embeddings offer un

agentsjerry-liu--x

Packora: Systematic Design for Generative Molecular Crystal Structure Prediction

arXiv:2608.26962v1 Announce Type: new Abstract: Molecular crystal structure prediction (CSP) is important in pharmaceuticals, agrochemicals, and organic electronics, where subtle differences in molecu

ProofEvolve: Neuro-Symbolic Evolution for Formal Automated Theorem Proving

arXiv:2608.26334v1 Announce Type: new Abstract: Automated theorem proving offers a natural foundation for recursive self-improvement in scientific discovery. However, existing neural provers do not fu

researcharxiv-cs-ai

Applications

Quantitative mapping from conventional MRI using self-supervised physics-guided deep learning: applications to a large-scale, clinically heterogeneous dataset

arXiv:2601.05063v2 Announce Type: replace-cross Abstract: Magnetic resonance imaging (MRI) is a cornerstone of clinical neuroimaging, yet conventional MRIs provide qualitative information heavily depe

applicationsarxiv-cs-cv

Rapid On-Robot Learning for Dynamic Manipulation Skills: Robot Juggling

arXiv:2608.26800v1 Announce Type: new Abstract: We present an online learning framework that enables a bimanual robot to acquire diverse juggling patterns directly on physical hardware within minutes,

local-aiarxiv-cs-ro

Real-time virtual circuits for plasma shape control via neural network emulators: integration and testing in the MAST-U PCS

arXiv:2608.26216v1 Announce Type: cross Abstract: The deployment of advanced, AI-enabled control algorithms in tokamak experiments requires robust integration with existing plasma control system (PCS)

RECAP-Forcing: Retaining Content Appearances for Long Video Generation

arXiv:2608.26671v1 Announce Type: new Abstract: Long autoregressive video generation faces a fundamental memory challenge: with a finite attention window, a model must decide which information from an

Ring Forcing: Towards Precise Long-Term Memory for Autoregressive Video Diffusion

arXiv:2608.26794v1 Announce Type: new Abstract: Scaling video generation to long durations reveals a critical bottleneck: current models lack robust long-term memory. This deficiency can be studied al

Safety by Design: Realized-Cost Constraints for Contextual Bandits with Continuous Actions

arXiv:2608.26755v1 Announce Type: new Abstract: Contextual bandits are a standard framework for sequential decision-making under uncertainty, with applications in clinical trials, dosage selection, re

Simple Actors and Deep Critics for Scalable Reinforcement Learning

arXiv:2608.26659v1 Announce Type: new Abstract: Recent progress in offline reinforcement learning (RL) has been driven by expressive generative actors such as diffusion and flow-matching policies, whi

Stack Trace-Based Crash Deduplication with Transformer Adaptation

arXiv:2508.19449v2 Announce Type: replace-cross Abstract: Automated crash reporting systems generate large volumes of duplicate reports, overwhelming issue-tracking systems and increasing developer wo

STEP: State-Aware Task Estimation and Planning with Multi-Modal LLMs for Human-Robot Collaboration

arXiv:2608.27225v1 Announce Type: cross Abstract: Effective human-robot collaboration in industrial settings requires robots to understand human intentions and assist with task planning, reducing work

researcharxiv-cs-ai

STITCH-OPE: Trajectory Stitching with Guided Diffusion for Off-Policy Evaluation

arXiv:2505.20781v2 Announce Type: replace-cross Abstract: Off-policy evaluation (OPE) estimates the performance of a target policy using offline data collected from a behavior policy, and is crucial i

TemporalFlow-VLA: Learning Physically Grounded Execution History for Long-Horizon Robot Manipulation

arXiv:2608.26821v1 Announce Type: new Abstract: Vision-language-action (VLA) models leverage pretrained vision-language representations for robot control, yet simply adding historical frames does not

researcharxiv-cs-ro

Tether the Subject, Release the Scene: Query-Aware Memory Routing for Long-Horizon Autoregressive Video Generation

arXiv:2608.26902v1 Announce Type: new Abstract: Streaming autoregressive video models generate long videos chunk by chunk, using historical memory to maintain consistency. Existing methods typically e

Ultra Low-Power, Lightweight, Probabilistic RSS-Based Path Reconstruction: A System for Landscape-Scale Bee Tracking

arXiv:2608.27152v1 Announce Type: new Abstract: Applications in fields such as movement ecology, Internet of Things or robotics share the need for systems that localize devices that are too small and

local-aiarxiv-cs-lg

UniFLM: United Segmentation and Measurement on Fetal Limb Ultrasonic Image

arXiv:2608.27240v1 Announce Type: new Abstract: Prenatal ultrasound examination is crucial for assessing fetal limb development and detecting congenital anomalies. However, existing artificial intelli

tutorialsarxiv-cs-cv

Using Poly-Encoders for Computationally Efficient Automated Creativity Assessment

arXiv:2608.26165v1 Announce Type: cross Abstract: Automated creativity assessment has been a long standing challenge, with traditional methods often being resource intensive or lacking practical accur

researcharxiv-cs-ai

Vagdhenu: A Vrutta (Meter) Aware Shloka-to-Chant (TTS) System for Sanskrit

arXiv:2608.26146v1 Announce Type: new Abstract: We present Vagdhenu, a vrutta (meter) aware shloka-to-chant system for Sanskrit: a text-to-speech system that maps a metrical verse to its chanted paray

researcharxiv-cs-cl

Video-FLAIR: Not Whether to Reason, But How

arXiv:2608.26495v1 Announce Type: new Abstract: Multimodal queries can require different types of reasoning. Some can be answered via perceptual reasoning, extracting information directly from the vis

What are the agentic softwares you run on top of local llm which can do tasks for you ?

What is your to software and why ? I am trying to learn first before I am pick a software. I already have Ollama and few models running which I can acces thru terminal and open web UI. My goal for now

local-air-ollama

Why Current XAI Is Not Enough for Arabic NLP: A Critical Survey of the Explainability Gap

arXiv:2608.26144v1 Announce Type: new Abstract: Explainable AI (XAI) is now a major theme in NLP; however, Arabic NLP remains under-explained in three connected senses. First, there is a method gap: A

researcharxiv-cs-cl

Why did My Robot Just Change Personality? Prompting Guidelines for a Grounded Robot Persona in LLM-Based HRI

arXiv:2608.26182v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for verbal interaction in social robots, yet prompt design in human-robot interaction (HRI) remains u

safetyarxiv-cs-ai

A Lightweight Multimodal Vision-Language Framework for Early-Stage Anatomical Green Fruit Classification in Commercial Orchards

arXiv:2608.24935v1 Announce Type: new Abstract: Accurate identification of early-stage apple fruitlet anatomical structures, including the calyx, fruitlet body, and peduncle, is essential for robotic

local-aiarxiv-cs-cv

Beyond Tokens: Probing Higher-Order Epistasis in Learned Protein Representations

arXiv:2608.24953v1 Announce Type: cross Abstract: Protein fitness landscapes contain nonlinear interactions in which mutation effects depend on other residues. We introduce ORBIT, an Order-Resolved Be

BRIDLE: Generalized Self-supervised Learning with Quantization

arXiv:2502.02118v2 Announce Type: replace-cross Abstract: Self-supervised learning has been a powerful approach for learning meaningful representations from unlabeled data across various domains, redu

CEDAR: Controlled and Event-Driven Demand Forecasting via Residual Decomposition

arXiv:2608.25871v1 Announce Type: new Abstract: Forecasting in large-scale e-commerce marketplaces is increasingly required to support planning: merchants need to evaluate sales outcomes under future

CVE-SAI: Counterfactual Visual Evidence-Guided Selective Attribute Indexing for Risk-Controlled E-commerce Search

arXiv:2608.25023v1 Announce Type: cross Abstract: Multimodal product models can complete missing e-commerce attributes, yet current methods still optimize attribute-answer accuracy without verifying v

local-aiarxiv-cs-cv

Deep greedy unfolding: Sorting out argsorting in greedy sparse recovery algorithms

arXiv:2505.15661v2 Announce Type: replace Abstract: Gradient-based learning imposes (deep) neural networks to be differentiable at all steps. This includes model-based architectures constructed by unr

Differentiated Aggregation to Improve Generalization in Federated Learning

arXiv:2404.11754v4 Announce Type: replace Abstract: This paper focuses on reducing the communication cost of federated learning by exploring generalization bounds and representation learning. We first

local-aiarxiv-cs-lg

Distance Is Not Enough: Forget-Retain Alignment Gap Predicts LLM Relearning Robustness

arXiv:2608.25429v1 Announce Type: cross Abstract: Machine unlearning aims to make a model forget specific data, yet unlearned LLMs often fail to stay unlearned: brief fine-tuning can revive removed kn

EgoArgus: Benchmarking VLMs as Situational Assistants for Modality-Grounded User Supports

arXiv:2608.25561v1 Announce Type: new Abstract: VLMs are increasingly positioned as daily assistants that perceive first-person environments, follow user dialogue, and decide how to help. Existing ego

safetyarxiv-cs-cl

Hardware

ExFold: Unified Expert Folding for Training-Free MoE Prefill-Decode Acceleration

arXiv:2608.24938v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models scale capacity for strong quality while keeping per-token compute bounded through sparse expert activation. Yet low-late

hardwarearxiv-cs-lg

Fast Generative Grasping via Lie Group-Constrained MeanFlow

arXiv:2608.26076v1 Announce Type: new Abstract: Grasp synthesis is a core task in robotic manipulation, for which the solution typically forms a multimodal distribution rather than a point estimate. G

tutorialsarxiv-cs-ro

Forge4D: Feed-Forward 4D Human Reconstruction and Interpolation from Uncalibrated Sparse-view Videos

arXiv:2509.24209v2 Announce Type: replace Abstract: Instant reconstruction of dynamic 3D humans from uncalibrated sparse-view videos is critical for numerous downstream applications. Existing methods,

FRAME: separating sampling variation from representational cause in medical imaging fairness

arXiv:2608.25981v1 Announce Type: new Abstract: Subgroup performance differences are the standard evidence for fairness bias in medical imaging, and the usual response removes the demographic informat

safetyarxiv-cs-cv

From Memorization to Absorption: Mixed-Policy RL for Continual Knowledge Injection

arXiv:2608.25243v1 Announce Type: new Abstract: Continual knowledge injection is essential for keeping large language models up-to-date in a fast-evolving world. Existing methods rely on supervised fi

safetyarxiv-cs-cl

GUIDE: Generative Unsupervised Chinese Query Correction via Phonetic and Visual Shared-ID Encoding

arXiv:2608.25343v1 Announce Type: new Abstract: Chinese query correction (CQC) is important for search and query recommendation on content platforms, but supervised methods rely on large annotated cor

tutorialsarxiv-cs-cl

Less Contouring, More Accuracy: Lesion-Guided ROI Deep Learning for Ovarian Ultrasound Classification

arXiv:2608.25965v1 Announce Type: new Abstract: Ovarian lesion classification using transvaginal ultrasound remains challenging due to overlapping imaging characteristics and the dependence on expert

Localize-Then-Decide Guarantees for LLM Judgments

arXiv:2608.25824v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as evaluators to assess output quality and preference alignment, yet providing reliable guarantees of

local-aiarxiv-cs-cl

LongVU-TTT: Causal Test-Time Training for Visual Resampling in Long Video Understanding

arXiv:2608.25729v1 Announce Type: new Abstract: Long-video MLLMs must model temporal change before a limited visual-token budget removes most frame evidence. We introduce LongVU-TTT, which inserts a c

Lowering the Barrier to AI-Driven Inspection: A No-Code Workflow for Automated Structural Defect Detection

arXiv:2608.25176v1 Announce Type: new Abstract: Structural health monitoring (SHM) is essential in modern engineering, providing data for condition-based maintenance, lifecycle assessment, and predict

Moving Beyond More Views: Redundancy-Aware Ego-Exo Fusion for Proficiency Estimation

arXiv:2608.25736v1 Announce Type: new Abstract: EgoExo proficiency estimation aims to assess action quality by integrating fine-grained motion cues from egocentric (1st-person) views with spatial cont

tutorialsarxiv-cs-cv