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Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling

arXiv:2606.27705v1 Announce Type: new Abstract: Large Language Models (LLMs) still struggle with the ``lost-in-the-middle'' problem, where critical information located in the middle of long-context in

safetyarxiv-cs-cl

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MixTTA: Low-Rank Cross-Channel Mixing for Reliable Test-Time Adaptation

DGX agent

arXiv:2606.28142v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) methods commonly update the affine parameters of normalization layers to adapt deployed models under distribution shifts. How

researcharxiv-cs-lg

29 Jun 2026

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

arXiv:2606.28027v1 Announce Type: cross Abstract: Neural video codecs have surpassed classical codecs in coding efficiency but remain impractical for deployment due to cross-platform incompatibility a

MobileManiBench: Simplifying Model Verification for Mobile Manipulation

model-releasesarxiv-cs-ro

arXiv:2602.05233v2 Announce Type: replace Abstract: Vision-language-action models have advanced robotic manipulation but remain constrained by reliance on the large, teleoperation-collected datasets d

ModaFlow: Modality-Aware Flow Matching for High-Fidelity Virtual Try-On

arXiv:2606.27773v1 Announce Type: new Abstract: Image-based virtual try-on has emerged as a compelling task in e-commerce and augmented reality, yet existing methods struggle to simultaneously preserv

safetyarxiv-cs-cv

Monocular Avatar Reconstruction via Cascaded Diffusion Priors and UV-Space Differentiable Shading

arXiv:2606.28144v1 Announce Type: new Abstract: Reconstructing high-fidelity, relightable 3D avatars from a single in-the-wild image is a challenging ill-posed problem, primarily hindered by the scarc

Monte Carlo with kernel-based Gibbs measures: Guarantees for probabilistic herding

arXiv:2402.11736v3 Announce Type: replace Abstract: Kernel herding belongs to a family of deterministic quadratures that seek to minimize the maximum mean discrepancy (MMD), that is, the worst-case in

Mosaic: A Benchmark Suite for Differentiable Physics Solvers

arXiv:2606.27895v1 Announce Type: cross Abstract: Differentiable partial differential equation (PDE) solvers underpin solver-in-the-loop ML training, gradient-based optimal control, and inverse proble

MPFlow: Multi-modal Posterior-Guided Flow Matching for Zero-Shot MRI Reconstruction

arXiv:2603.03710v3 Announce Type: replace-cross Abstract: Zero-shot MRI reconstruction relies on generative priors, but single-modality unconditional priors produce hallucinations under severe ill-pos

Multi-Modal Conditioned High-Resolution Transformer for Urban Electromagnetic Field Map Prediction Download PDF

arXiv:2606.27671v1 Announce Type: new Abstract: Predicting electromagnetic field (EMF) strength in urban environments is essential for cellular network planning but computationally expensive with phys

MultiHashFormer: Hash-based Generative Language Models

arXiv:2606.28057v1 Announce Type: cross Abstract: Language models (LMs) represent tokens using embedding matrices that scale linearly with the vocabulary size. To constrain the parameter footprint, pr

Multimodal Evaluator Preference Collapse: Cross-Modal Coupling in Self-Evolving Agents

model-releasesarxiv-cs-cl

arXiv:2606.16682v3 Announce Type: replace-cross Abstract: When AI agents use language models to evaluate their own outputs in a feedback loop, systematic biases emerge. We show that Evaluator Preferen

MVGS: Multi-view Regulated Gaussian Splatting for Novel View Synthesis

arXiv:2410.02103v4 Announce Type: replace Abstract: Recent works in volume rendering, extit{e.g.} NeRF and 3D Gaussian Splatting (3DGS), significantly advance the rendering quality and efficiency with

MVPruner: Dynamic Token Pruning for Accelerating Multi-view Vision-Language Models in Autonomous Driving

arXiv:2606.27660v1 Announce Type: new Abstract: Vision-Language Models (VLMs) improve generalization and interpretability in autonomous driving but suffer from efficiency issues due to long visual tok

Narrative-UFET: Narrative Generation for Ultra-Fine Entity Typing

arXiv:2606.27598v1 Announce Type: cross Abstract: Ultra-fine entity typing (UFET) assigns highly specific types to entity mentions, but current approaches struggle with types in the long tail. We hypo

NLL-Guided Full-Attention Layer Selection for Training-Free Sliding-Window Adaptation

arXiv:2606.27791v1 Announce Type: cross Abstract: Hybrid attention models that mix full and sliding-window attention across layers offer a promising approach to efficient long-context inference, but t

Non-Linear Model-Based Sequential Decision-Making in Agriculture

arXiv:2509.01924v4 Announce Type: replace-cross Abstract: Agricultural decision-making faces a dual challenge: sustaining high yields to meet global food security needs while reducing the environmenta

applicationsarxiv-cs-lg

Non-Linear Strategic Classification Made Practical

arXiv:2606.28204v1 Announce Type: cross Abstract: Algorithmic developments in Strategic Classification have been mostly limited to linear classifiers in settings where the best response has a closed-f

researcharxiv-cs-lg

NormAct: A Benchmark for Hidden Social Norm Compliance in Embodied Planning

arXiv:2606.27826v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly deployed as embodied planners in egocentric environments, where task success requires not only

NormGuard: Reward-Preserving Norm Constraints in Flow-Matching Reinforcement Learning

arXiv:2606.27771v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training improves the reward alignment of flow-based generators, but often degrades perceptual quality in ways that a

local-aiarxiv-cs-cv

Not All Relations Rotate Alike: Transformation-Aware Decoupling for Viewpoint-Robust 3D Scene Graph Generation

arXiv:2606.27412v1 Announce Type: cross Abstract: 3D Scene Graph Generation (3DSGG) represents 3D scenes as structured object-relation-object graphs, providing a compact relational abstraction for spa

Odyssey: Constructing Verifiable Local Truth-Preserving Foundation Models

arXiv:2606.27593v1 Announce Type: new Abstract: We introduce a categorical framework called ODYSSEY for constructing verifiable, local truth-preserving foundation models as compositions of foundries:

local-aiarxiv-cs-ai

Tutorials

On the Effect of Uncertainty on Layer-wise Inference Dynamics

arXiv:2507.06722v2 Announce Type: replace Abstract: Understanding how large language models (LLMs) internally represent and process their predictions is central to detecting uncertainty and preventing

tutorialsarxiv-cs-cl

On the Inseparability of Instructions and Data in Shared-Embedding Sequence Models

arXiv:2606.27567v1 Announce Type: cross Abstract: Prompt injection is the top security risk for LLM-integrated applications, yet every defense proposed so far has been broken. We prove this is not a c

On the stability of scale-space metrics

arXiv:2606.27605v1 Announce Type: cross Abstract: We study the stability of a classical family of metrics defined over functions' Gaussian scale-space representations, focusing on the comparison of im

Ontology-Guided Evidence Path Inference for Multi-hop Knowledge Graph Question Answering

arXiv:2606.28076v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) aims to answer natural-language questions by reasoning over structured facts. Existing multi-hop KGQA methods

Operator Learning for Cubic Nonlinear Schrodinger Equation on Periodic Domains

arXiv:2606.27459v1 Announce Type: new Abstract: We consider the cubic nonlinear Schrodinger (NLS) equation on two-dimensional flat tori with varying aspect ratios. In this formulation, the choice of a

OperatorSHAP: Fast and Accurate Shapley Value Estimation for Neural Operators

arXiv:2606.28065v1 Announce Type: cross Abstract: Understanding model predictions is essential for physical applications, where outputs often inform safety-critical decisions, such as structural load

Optimizing Teacher-Student Partitioning for Scalable Knowledge Distillation on HPC Systems

arXiv:2606.27797v1 Announce Type: cross Abstract: Knowledge Distillation (KD) enables training smaller student models under the guidance of larger teacher models, and the widely adopted TRL library im

applicationsarxiv-cs-ai

Agents

Orientation Matters: Learning Radiation Patterns of Multi-Rotor UAVs In-Flight to Enhance Communication Availability Modeling

arXiv:2604.02827v2 Announce Type: replace Abstract: The paper presents an approach for learning antenna Radiation Patterns (RPs) of a pair of heterogeneous quadrotor Uncrewed Aerial Vehicles (UAVs) by

agentsarxiv-cs-ro

OrthoTryOn: Geometric Orthogonalization for Conflict-Free Unified Fashion Generation

arXiv:2606.27880v1 Announce Type: new Abstract: Unified fashion generation integrates tasks like virtual try-on and garment reconstruction into a single model to reduce task-specific adaptation costs.

OSOR: One-Step Diffusion Inpainting for Effect-Aware Object Removal

arXiv:2606.28094v1 Announce Type: cross Abstract: Real-world object removal is challenging due to two key difficulties: the target object's non-local effects, such as shadows and reflections, which ar

local-aiarxiv-cs-ai

Output-Space Allocation Costs for Calibration-Guided LLM Compression: An Empirical Study

arXiv:2606.27785v1 Announce Type: cross Abstract: Training-free compression methods for large language models (LLMs) often use calibration data to guide compression decisions. ROCKET, a recent method

OverFlowLight: Real-Time Gridlock Prevention and Traffic Signal Optimization for Urban Intersections

arXiv:2606.27381v1 Announce Type: cross Abstract: Queue overflow, a severe consequence of urban traffic congestion, occurs when vehicle queues exceed intersection capacity, obstructing upstream traffi

P-ARC: Exploiting Subproblem Independence for Parallel Multi-Robot Motion Planning

arXiv:2606.27625v1 Announce Type: new Abstract: This paper presents Parallel ARC (P-ARC), a parallel variant of the Adaptive Robot Coordination (ARC) approach to multi-robot motion planning (MRMP). P-

applicationsarxiv-cs-ro

PA-BiCoop: A Primary-Auxiliary Cooperative Framework for General Bimanual Manipulation

arXiv:2606.28192v1 Announce Type: new Abstract: Bimanual manipulation is essential for advanced robotic systems because it offers higher efficiency and flexibility compared to single-arm configuration

applicationsarxiv-cs-ro

PAC-Bayesian Certificates for Quadratic Closed-Loop Control

arXiv:2606.28281v1 Announce Type: cross Abstract: PAC-Bayesian bounds provide finite-sample guarantees for data-dependent randomized predictors, but applying them to learning-based control is difficul

researcharxiv-cs-lg

Tutorials

PairSAE: Mechanistic Interpretability from Pair Representations in Protein Co-Folding

arXiv:2606.27440v1 Announce Type: new Abstract: Foundation models for structural biology have achieved remarkable performance in predicting biomolecular structure and show promise for the design of pr

tutorialsarxiv-cs-lg

Panoramic Scene Analysis: A Survey from Distortion-Aware Engineering to Sphere-Native Foundation Modeling

arXiv:2606.27745v1 Announce Type: new Abstract: Panoramic images capture the complete visual sphere in a single frame, providing spatial context unattainable by conventional cameras. Yet this complete

Parallel Rollout Approximation for Pixel-Space Autoregressive Image Generation

arXiv:2606.27978v1 Announce Type: cross Abstract: Pixel-space continuous-token autoregressive (AR) generation directly models images as sequences of raw pixel patches, avoiding discrete tokenization o

Parameter-Efficient Continuous-Variable Photonic Quantum Neural Networks for Edge Quantum AI: Demonstration in Oral Cancer Detection

arXiv:2606.28252v1 Announce Type: cross Abstract: Early detection of oral cancer markedly improves clinical outcomes, yet specialized diagnostic tools remain scarce in low-resource settings. Smartphon

Parameter Efficient Hybrid Transformer (PEHT) for Network Traffic Prediction via Dynamic Urban Congestion Integration

arXiv:2606.28274v1 Announce Type: cross Abstract: Accurate network traffic prediction is a critical element for efficient resource allocation in dynamic urban cellular networks. However, prediction re

Parameter-Efficient Quantum-Inspired Fast Weight Programmers for Traffic-Matrix Forecasting

arXiv:2606.27821v1 Announce Type: cross Abstract: Traffic matrices (TMs) capture network-wide origin-destination demand and are central to traffic engineering, yet accurate whole-matrix forecasting re

PEBS: Per-rater Empirical-Bayes Shrinkage for RLHF Reward-Model Calibration

arXiv:2606.27578v1 Announce Type: cross Abstract: Reward models for Reinforcement Learning from Human Feedback (RLHF) pool preferences across thousands of annotators and fit one global affine calibrat

Pepti-drift: Toxicity-Repulsive Drifting for Antigen-Conditioned Discrete Peptide Generation

arXiv:2606.27824v1 Announce Type: cross Abstract: Peptides are a promising therapeutic modality that combine the chemical tunability of small molecules with the target specificity of macromolecular th

PerceptionRubrics: Calibrating Multimodal Evaluation to Human Perception

arXiv:2606.28322v1 Announce Type: new Abstract: We introduce PerceptionRubrics, a rubric-based evaluation framework that addresses the gap between saturated benchmark scores and real-world brittleness

Perceptual 3D Simulation With Physical World Modeling

arXiv:2606.27575v1 Announce Type: new Abstract: Predicting how a scene will evolve after a desired 3D transformation from images is a central goal in vision, graphics, and robotics. Yet unlike ideal s

local-aiarxiv-cs-cv

Permutation Learning with Only N Parameters: From SoftSort to Self-Organizing Gaussians

arXiv:2503.13051v3 Announce Type: replace-cross Abstract: Sorting and permutation learning are key concepts in optimization and machine learning, especially when organizing high-dimensional data into