Search: “models”

OneShot: Index-in-Ranking with Neural Scoring for Large-Scale Retrieval

arXiv:2607.27475v1 Announce Type: cross Abstract: In modern recommendation systems, retrieval serves as a primary stage responsible for filtering billions of candidate items down to thousands prior to

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Physical prior guided cooperative learning framework for joint turbulence degradation estimation and infrared video restoration

DGX agent

arXiv:2408.04227v2 Announce Type: replace-cross Abstract: Infrared imaging and turbulence strength measurements are in widespread demand in many fields. This paper introduces a Physical Prior Guided C

researcharxiv-cs-cv

31 Jul 2026

Real-Time Hard Peak Age-of-Information Safety with No-Regret Learning

arXiv:2607.27626v1 Announce Type: new Abstract: Safety-critical IoT systems such as industrial closed-loop control, V2X coordination, and remote teleoperation require every sensor's peak Age of Inform

ReDiPPO: Reference-Guided Value Calibration and Discrepancy-Aware Token Reweighting for Mathematical Reasoning

arXiv:2607.27631v1 Announce Type: cross Abstract: Reinforcement learning has emerged as an effective paradigm for enhancing the mathematical reasoning capabilities of large language models. Among exis

safetyarxiv-cs-cl

Regularizing modality contribution drift in multimodal continual learning

arXiv:2607.27260v1 Announce Type: new Abstract: Multimodal continual learning (MMCL) aims to learn emerging knowledge from multimodal data while preserving knowledge. To mitigate forgetting, current M

Robust Wavelength Selection for Partial Least Squares Sugar Content Estimation Using Combinatorial Bayesian Optimization

arXiv:2607.27645v1 Announce Type: cross Abstract: Wavelength selection is one of the important preprocessing methods in near-infrared spectroscopy to improve prediction accuracy and interpretability o

Same Branches, Different Trees: A Bifurcation Connectedness Metric for Coronary Artery Segmentation and FFR-CT Decision Agreement

arXiv:2607.28327v1 Announce Type: new Abstract: Fractional flow reserve derived from CT angiography (FFR-CT) simulates flow through a patient-specific vessel model, so its accuracy depends on the conn

Search Strategies for Optimal Classification and Regression Trees

arXiv:2607.28170v1 Announce Type: new Abstract: Optimal decision trees (ODTs) are compact, interpretable machine learning models that globally optimize a given objective, but their scalability remains

SharedAssembly: A Data Collection Approach via Shared Tele-Assembly

arXiv:2503.12287v2 Announce Type: replace Abstract: High-precision, tight-clearance assembly demonstrations are indispensable for training tactile-aware robotic foundation models, yet their acquisitio

applicationsarxiv-cs-ro

Hardware

Simulation of Surgical Suturing Using Position-Based Dynamics and the Material Point Method for Robot Reinforcement Learning

arXiv:2607.27494v1 Announce Type: new Abstract: Recent advances in robotics research have created a strong demand for high-performance simulators. Surgical robotics simulation faces unique challenges

hardwarearxiv-cs-ro

Agents

Sources: OpenAI has discovered other instances where AI agents escaped containment; none of the agents were thought to have left OpenAI's network (Reuters)

Reuters: Sources: OpenAI has discovered other instances where AI agents escaped containment; none of the agents were thought to have left OpenAI's network — OpenAI has discovered other instances in wh

agentstechmeme

TIER-MoE: Trust-Informed Expert Routing via Conditional Modality Risk for Multimodal Fusion in Biomedical Classification

arXiv:2607.27289v1 Announce Type: new Abstract: The promise of multimodal fusion lies in combining complementary sources of evidence, yet more evidence does not always yield a better prediction. Recen

TongueReenact: Geometry-Anchored Tongue Synthesis for Face Reenactment

arXiv:2607.28039v1 Announce Type: new Abstract: Modern face reenactment systems achieve impressive pose and expression transfer using geometry-driven representations. However, they largely ignore tong

Train Small, Deploy Large: Zero-Shot GNN Transfer Through Geometric Renormalization

arXiv:2607.27767v1 Announce Type: new Abstract: Graph neural networks (GNNs) can operate on large graphs but become infrastructure-sensitive at the scale of millions of nodes and typically require sca

applicationsarxiv-cs-lg

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards

arXiv:2511.23310v3 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as an effective paradigm for post-training large language models, yet the de

VisualRouter: Query-Grounded Visual Sampling for Long Video Understanding

arXiv:2607.28463v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have achieved significant progress in video understanding, yet understanding long videos remains challenging due to

What am I doing wrong in my LoRA training?

local-air-stablediffusion

Hi everyone, this is my very first time training a LoRA, so I might be missing something basic! I trained an art style LoRA using noobaiXLNAIXL_vPred10Version as the base model, with 21 images, 8 epoc

A Compositional Theory of Causally Masked Transformers

arXiv:2607.26988v1 Announce Type: cross Abstract: What types of decision problems can a causally masked, finite-precision transformer solve for inputs of arbitrary length? Existing answers often rely

Adaptive Gradient-Based Methods for a Broader Class of Optimization Problems under Performative Prediction

arXiv:2607.26562v1 Announce Type: cross Abstract: We study optimization under performative prediction, where deploying a model affects the future data distribution. For this setting, several gradient-

Adaptively Robust LLM Monitoring via Activation Watermarking

arXiv:2603.23171v3 Announce Type: replace-cross Abstract: Providers monitor deployed large language models (LLMs) to detect misuse that they cannot prevent. LLM monitoring is deterministic and often o

local-aiarxiv-cs-lg

AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis

arXiv:2504.19621v2 Announce Type: replace Abstract: Machine learning (ML) systems for medical imaging have demonstrated remarkable diagnostic capabilities, but their susceptibility to biases poses sig

Hardware

BATS: Resource-Efficient Volumetric Segmentation with Boundary-Aware Mixed-Resolution Tokens

arXiv:2607.26829v1 Announce Type: new Abstract: Many high-performing volumetric segmentation models maintain dense multi-scale feature maps, leading to high activation memory and inference cost. We pr

hardwarearxiv-cs-cv

Hardware

Can AI agents conduct open-ended AI research? Most evaluations of agents conducting AI research focus on narrow, verifiable tasks. But AI re…

Can AI agents conduct open-ended AI research? Most evaluations of agents conducting AI research focus on narrow, verifiable tasks. But AI research is often open ended. Researchers pick hypotheses, dec

hardwareyann-lecun--x

Cohere has joined @NVIDIA alongside industry leaders in founding the Open Secure AI Alliance. Everybody should have the capability to keep t…

Cohere has joined @NVIDIA alongside industry leaders in founding the Open Secure AI Alliance. Everybody should have the capability to keep their infrastructure secure. Everybody deserves access to mod

safetycohere--x

Do Methods Support the Claims? Intra-Paper Verification for Peer Review

arXiv:2607.26066v1 Announce Type: new Abstract: The growing volume of scientific submissions has motivated interest in using large language models (LLMs) to assist peer review. Existing automated nove

safetyarxiv-cs-cl

Agents

DREvo: Distilling Recalibrated Historical Experience for Harness Self-Evolution

arXiv:2607.26722v1 Announce Type: cross Abstract: Harness plays a critical role in large language model agent performance, and building a high-performing harness requires substantial expert effort. Th

agentsarxiv-cs-lg

Enfold: Folding World-Generator Computation into Predictive Representations for Efficient Embodied Control

arXiv:2607.26657v1 Announce Type: new Abstract: World generative models are typically used through what they produce: a rendered future, a video-conditioned action, or latent context computed by a cos

researcharxiv-cs-ro

Explainable and Resource-Efficient Spatial Reasoning in Multimodal LLMs for Decision-Critical Applications

arXiv:2607.27145v1 Announce Type: new Abstract: As Multimodal Large Language Models (MLLMs) are increasingly deployed in decision-critical pipelines such as robotics, embodied AI, and safety monitorin

safetyarxiv-cs-cv

FakeIDet3-DB: Refining Digital Attacks and Patch Extraction for Secure ID Benchmarking

arXiv:2607.26641v1 Announce Type: new Abstract: Identity document (ID) authentication relies on the structural integrity of complex, high-frequency security patterns. However, advanced Generative AI m

local-aiarxiv-cs-cv

Agents

Filesystem-Based Memory for LLM Agents: Organization, Evolution, and Sustainability

arXiv:2607.26637v1 Announce Type: new Abstract: Deployed LLM agents increasingly keep their long-term memory as a filesystem: a directory tree of markdown files that the agent itself reads, writes, an

agentsarxiv-cs-cl

FreqForcing: Autoregressive Long Video Generation via Spectral Self-Anchoring

arXiv:2607.27110v1 Announce Type: new Abstract: Autoregressive video diffusion models enable real-time streaming video generation. However, errors introduced during self-rollout accumulate over long h

From Representations to Behaviors: Exploring the Person-Situation-Behavior Triad in LLMs

arXiv:2607.26853v1 Announce Type: new Abstract: Human personality theories characterize traits not as isolated attributes captured by a single score, but as stable individual tendencies expressed thro

researcharxiv-cs-cl

From Spatial Semantics to Temporal Context: Leveraging Gaze Trajectory for Weakly Supervised Medical Image Segmentation

arXiv:2607.26542v1 Announce Type: new Abstract: Medical image segmentation heavily depends on labor-intensive and time-consuming pixel-level annotations. Eye tracking offers a cost-effective solution

Generation or Judgement? A Paradigm Perspective on LLM-Based Emotion-Cause Pair Extraction in Conversation

arXiv:2607.26967v1 Announce Type: new Abstract: Emotion-cause pair extraction in conversation (ECPEC) identifies utterance pairs in which one utterance causes an emotion expressed in another. Recent L

researcharxiv-cs-cl

HERMES: A Hybrid Ensemble for Head-and-Neck Tumor Segmentation, TN Staging, and Recurrence-Free Survival on PET/CT

arXiv:2607.26498v1 Announce Type: new Abstract: We present HERMES (Hybrid Ensemble for Radiotherapy-target segmentation, Malignancy staging, and Event-free Survival), a single containerized algorithm

Incast-Free MoE Rate-Based Scheduling

arXiv:2607.26340v1 Announce Type: cross Abstract: Mixture of Experts (MoE) architectures have become key to large language models; however, their typical round-robin (RR) scheduling introduces signifi

Is it possible to have multiple concept in one LORA?

local-air-stablediffusion

I have question. I am trying to train a LORA, and my concept is for Indian wedding and tradional wardrobe based on Regions. I was planning to train a model which understand each region clothing style

Kinetic Mining in Context: Few-Shot Action Synthesis via Text-to-Motion Distillation

arXiv:2512.11654v3 Announce Type: replace Abstract: The acquisition cost for large, annotated motion datasets remains a critical bottleneck for skeletal-based Human Activity Recognition (HAR). Althoug

Latent-IM: Latent Interaction Management for Speech LLMs

arXiv:2607.26928v1 Announce Type: new Abstract: Classical spoken dialogue systems often separated dialogue management from response realization: a policy selected the next dialogue action, and a gener

safetyarxiv-cs-cl

LLM-Grounded Dynamic Task Planning with Hierarchical Temporal Logic for Human-Aware Multi-Robot Handover

arXiv:2602.09472v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) enable non-experts to specify open-world multi-robot tasks, but the generated plans are often kinematically infea

Making Implicit Premises Explicit in Logical Understanding of Enthymemes

arXiv:2603.06114v2 Announce Type: replace Abstract: Real-world arguments in text and dialogues are normally enthymemes (i.e. some of their premises and/or claims are implicit). Natural language proces

applicationsarxiv-cs-cl

MLVC: Multi-platform Learned Video Codec for Real-World Deployment [P]

applicationsr-machinelearning

I've always found it a little strange that AI is everywhere, but the codecs we use in practice are the traditional hand-engineered systems like h.264, h.265, av1. Alexnet started the wave of neural ne

On the robustness of noisy solutions in non-convex neural networks

arXiv:2607.27000v1 Announce Type: cross Abstract: Optimization in non-convex neural network models is strongly influenced by the geometry of the solution space: sparse, isolated, point-like clusters a

Pangram 4 Technical Report

arXiv:2607.27183v1 Announce Type: new Abstract: We present Pangram 4, the latest deep-learning-based AI-text classification model from Pangram Labs. We achieve an AUROC of 0.9916 with a false positive

researcharxiv-cs-cl

Particle-Filtering-based Latent Diffusion for Inverse Problems

arXiv:2408.13868v2 Announce Type: replace Abstract: Current strategies for solving image-based inverse problems apply latent diffusion models to perform posterior sampling.However, almost all approach

PIKS: Universal Physics-Informed Kernel Methods

arXiv:2607.27062v1 Announce Type: cross Abstract: Physics-informed machine learning incorporates physical principles --often expressed via differential operators-- into data-driven models. While physi

Quantized Kimi-K3:cloud

I’m on the $20 plan and I’m not going to pay for extra usage credits to use Kimi-K3. Could the folks at Ollama quantize the model and serve it up in the cloud? submitted by /u/EvanstonNU [link] [comme

local-air-ollama

RA-Det: Towards Universal Detection of AI-Generated Images via Robustness Asymmetry

arXiv:2603.01544v2 Announce Type: replace Abstract: Recent image generators produce photo-realistic content that undermines the reliability of downstream recognition systems. As visual appearance cues