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iFAN: Inference-Aware Learning for Plain Mask Transformers

arXiv:2608.03216v1 Announce Type: new Abstract: Query-based mask transformers assemble segmentation outputs through pixel-wise competition among query predictions of the final layer, yet this inferenc

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IRIS: Visual-Semantic Binding for Forgery-Resistant Watermarking of Diffusion Images

DGX agent

arXiv:2608.03539v1 Announce Type: new Abstract: Most in-generation diffusion watermarks embed patterns independent of the image that carries them, and attackers transplant the marks onto images the ge

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5 Aug 2026

Language Models Encode the Contextual Truth of Propositions

arXiv:2608.03035v1 Announce Type: new Abstract: Prior work has shown that LLMs encode the truth of factual propositions along linear directions in activation space. It's unclear how these representati

Learning a Vector-Symbolic Model for Socio-Cultural Tasks

arXiv:2608.02807v1 Announce Type: cross Abstract: How can we better represent the impact of sociocultural structures on decision making in computational cognitive models? Modeling this impact requires

Learning Biomechanically Plausible Human Motion from Sparse Radar Point Clouds

arXiv:2608.03637v1 Announce Type: new Abstract: Radar-based human pose estimation has focused on improving learning algorithms while representing the body as unconstrained keypoint coordinates. We add

LiteMVS: Efficient Multi-View Stereo with Foundation Distillation and Expert Aggregation

arXiv:2608.03851v1 Announce Type: new Abstract: Real-time 3D perception is crucial for robotics, augmented reality, and embodied intelligence applications. Existing multi-view stereo (MVS) methods pri

LLaDA MoE v2: Scaling Mixture-of-Experts Diffusion Language Models

arXiv:2608.03457v1 Announce Type: new Abstract: Diffusion language models (dLLMs) offer an alternative to autoregressive (AR) language modeling, yet the scaling behavior of Mixture-of-Experts (MoE) dL

LLMs Can Annotate Attribution Graphs

arXiv:2608.02632v1 Announce Type: new Abstract: Circuit tracing is an exciting technique for revealing the internal computation of language models, but it requires a time-intensive manual step of grou

Logic Before Language: Pre-pretraining on Formal Derivations Fosters Skill Acquisition and Compressibility

arXiv:2608.03930v1 Announce Type: cross Abstract: Pre-pretraining language models (LMs) on symbolic data can accelerate and improve natural language acquisition. However, existing pre-pretraining task

Mapping the City Through the Lens of Language Models

arXiv:2608.02971v1 Announce Type: new Abstract: Language models often complete an underspecified reference to a city with unstated assumptions about urban size, form, infrastructure, environment, and

MDLMPE: Distribution Aware Positional Encoding for Masked Diffusion Language Models

arXiv:2608.03769v1 Announce Type: cross Abstract: Masked diffusion language models (MDLMs) enable parallel generation and bidirectional context modeling, but their positional context differs fundament

Mechanism of Task-oriented Information Removal in In-context Learning

arXiv:2509.21012v4 Announce Type: replace-cross Abstract: In-context Learning (ICL) is an emerging few-shot learning paradigm based on modern Language Models (LMs), yet its inner mechanism remains unc

MissClick: Exploiting Digit-Serialized Coordinates to Attack GUI Grounding Models

arXiv:2608.03740v1 Announce Type: new Abstract: Recent GUI visual grounding models generate screen coordinates as sequences of digit tokens that are parsed into numerical values and mapped to executab

Modeling Matches as Language: A Generative Transformer Approach for Counterfactual Player Valuation in Football

arXiv:2603.15212v2 Announce Type: replace Abstract: Evaluating football player transfers is challenging because player actions depend strongly on tactical systems, teammates, and match context. Despit

MoECa: Aligning Feature Reuse with Expert Decomposition in Diffusion Transformers

arXiv:2606.15615v2 Announce Type: replace-cross Abstract: Diffusion Transformers with Mixture-of-Experts (DiT-MoE) improve model capacity under sparse activation, but diffusion inference is still bott

MSTAR: Multi-Scale Backbone Architecture Search for Timeseries Classification

arXiv:2402.13822v2 Announce Type: replace Abstract: Most of the previous approaches to Time Series Classification (TSC) highlight the significance of receptive fields and frequencies while overlooking

MuEvo: LLM-Driven Evolution of Multi-Heuristic Ensemble

arXiv:2608.03636v1 Announce Type: cross Abstract: Large language model-based automated heuristic design (LLM-AHD) has shown strong potential in discovering effective heuristics for combinatorial optim

Multi-Camera Trajectory Forecasting with Trajectory Tensors

arXiv:2108.04694v2 Announce Type: cross Abstract: We introduce the problem of multi-camera trajectory forecasting (MCTF), which involves predicting the trajectory of a moving object across a network o

Multi-Task Multi-Frame Visual Piano Transcription

arXiv:2608.03419v1 Announce Type: cross Abstract: Audio-based piano transcription performs well on onset, pitch, and velocity, but the sustain pedal lets sound persist long after key release, so audio

Multimodal Auto-regressive Transformer Surrogate for Modeling Variable Operations and Quantifying Uncertainty in Geological Carbon Storage

arXiv:2608.02629v1 Announce Type: cross Abstract: The use of variable well perforation and injection strategies can improve the efficiency of geological carbon storage operations. We develop a new mul

Multimodal Plant Root Phenotyping with Integration of 3D Skeleton Extraction and Language Analysis

arXiv:2608.03109v1 Announce Type: new Abstract: Plant root phenotyping is fundamental to understanding below-ground structures, optimizing crop management, and improving agricultural sustainability. T

Muon Meets Mamba: Spectral Optimization for State Space Models

arXiv:2608.03941v1 Announce Type: new Abstract: Muon is a recent optimizer that orthogonalizes the update to each weight matrix with a Newton-Schulz iteration, which performs steepest descent under th

NANQ: Noise-Floor-Aware Mixed-Precision Non-Uniform Quantization for Analog Compute-in-Memory

arXiv:2608.02700v1 Announce Type: cross Abstract: Analog compute-in-memory (CIM) enables energy-efficient neural network inference, but device variation and read noise can severely degrade low-bit qua

NCGR: Noise-Conditional Gated Rectification for Camera Extrinsic Perturbations in BEV 3D Object Detection

arXiv:2608.03895v1 Announce Type: new Abstract: Camera-based bird's-eye-view (BEV) 3D detection typically assumes accurate and fixed camera extrinsics. In detectors using spatial cross-attention (SCA)

Neural network realization of binary refinement iterates via a two-chart atlas selector

arXiv:2608.02624v1 Announce Type: cross Abstract: Refinement operators generate many functions used in wavelet constructions, subdivision schemes, and geometric modeling. Their finite iterates can dev

Noise-Aware Shrinkage for Differentially Private Zeroth-Order Fine-Tuning of Large Language Models

arXiv:2608.03277v1 Announce Type: new Abstract: Differentially private zeroth-order optimization (DP-ZO) enables memory-efficient private fine-tuning of large language models using only forward evalua

Non-Destructive Quantification of Urea Adulteration in Bovine Milk Using Transmittance Multispectral Imaging

arXiv:2608.03113v1 Announce Type: new Abstract: Adulteration of bovine milk using urea remains a major food quality and health concern, motivating the development of rapid and quantitative screening t

OmniPack: Unified Token Compression for Efficient Omni-modal Large Language Models

arXiv:2608.03812v1 Announce Type: new Abstract: Omni-modal large language models (Omni-LLMs) have achieved remarkable performance on audio-visual understanding tasks, but processing long and highly re

On the Diversity of Analogy Making in Large Language Models

arXiv:2608.03233v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable potential for analogy making, a core cognitive capability that drives novelty and creativity.

On the Non-Specificity of Statistical Measures Used in Script Decipherment

arXiv:2608.02999v1 Announce Type: new Abstract: Statistical regularities are routinely offered as evidence that undeciphered sign systems encode language; the Indus script debate is the canonical exam

On the Performance of Malware Detection Classifiers Using Hardware Performance Counters

arXiv:2608.02671v1 Announce Type: cross Abstract: Malware detection using Hardware Performance Counters (HPC) has emerged as a promising solution to improve the security of computing systems as a comp

Open-Linguistic Concept Unified Learning for Cross-Site Interpretable Dermatology Image Diagnosis

arXiv:2608.03225v1 Announce Type: new Abstract: Human-interpretable computer-aided diagnosis is crucial for clinical decision making. Concept-based models excel by providing transparent reasoning and

Output-Aware Rotation for INT2 KV-Cache Quantization

arXiv:2608.02691v1 Announce Type: cross Abstract: The key-value (KV) cache has become a major memory and bandwidth bottleneck in long-context large language model inference, making ultra-low-bit quant

PAMT: Process-Aligned Reinforcement Learning for Multi-Domain Machine Translation

arXiv:2608.03077v1 Announce Type: new Abstract: Multi-domain machine translation (MDMT) requires more than fluent generation: it demands domain-sensitive translation decisions such as domain disambigu

PASE: Leveraging the Phonological Prior of WavLM for Low-Hallucination Generative Speech Enhancement

arXiv:2511.13300v1 Announce Type: cross Abstract: Generative models have shown remarkable performance in speech enhancement (SE), achieving superior perceptual quality over traditional discriminative

PDD-RRG: Posterior Diagnostic Decision for Study-level Radiology Report Generation

arXiv:2608.03055v1 Announce Type: cross Abstract: Automatic radiology report generation (RRG) aims to simulate the workflow of radiologists, assisting them in clinical diagnosis. However, existing met

pi-Attention: Online Efficient Sparse Transformers for Long-Context Modeling

arXiv:2511.10696v3 Announce Type: replace-cross Abstract: Sparse attention is crucial in long-context Transformers, which restricts each token to a limited neighborhood and thereby reduces the quadrat

PixelUp: Zero-Shot Semantic Feature Upsampling for Fine-Grained Vision Tasks

arXiv:2608.02792v1 Announce Type: new Abstract: Self-supervised Vision Foundation Models (VFMs) have become essential backbones for downstream tasks due to their strong and transferable visual represe

POEM: Phase-Aware SO(2) Feature Rotation for Time Series Forecasting Under Periodicity Drift

arXiv:2608.03630v1 Announce Type: new Abstract: Deep learning has advanced time series forecasting, but periodicity drift, in which cycle timing and phase vary over time, remains a challenging problem

PolyLayout: Multi-room Manhattan Layout Estimation

arXiv:2608.03323v1 Announce Type: new Abstract: Estimating room layouts from multi-view imagery is a core task for indoor scene understanding. Existing methods are typically limited either by poor gen

Predicting Deep Neural Network Training Outcomes from Early Training Telemetry

arXiv:2608.03709v1 Announce Type: new Abstract: Large hyperparameter sweeps for deep neural networks spend substantial compute on configurations that are effectively doomed from the first few epochs.

Predictive Set Theory: A Generative Framework for Cognitive Architecture with Operationalized Core Mechanisms

arXiv:2608.02704v1 Announce Type: new Abstract: Predictive processing theories portray the brain as a hierarchical prediction engine that minimizes prediction error, yet they lack operational definiti

PRIVEE: Privacy-Preserving Vertical Federated Learning Against Feature Inference Attacks

arXiv:2512.12840v2 Announce Type: replace-cross Abstract: Vertical Federated Learning (VFL) enables collaborative model training across organizations that share common user samples but hold disjoint f

Quality Control Algorithms for Pattern Counting

arXiv:2608.03439v1 Announce Type: cross Abstract: In recent work, Marcussen, Rubinfeld, and Sudan introduced the notion of quality control problems, which aim to capture the task of determining if a g

Recurrent Contrastive Learning for Imbalanced Medical Image Classification

arXiv:2608.03304v1 Announce Type: new Abstract: Medical image classification often suffers from class imbalance due to the inherent disparities in disease incidence. Existing approaches, such as class

Robust Biharmonic Skinning Using Geometric Fields

arXiv:2406.00238v3 Announce Type: replace-cross Abstract: Bounded bihramonic weights are a popular tool used to rig and deform characters for animation, to compute reduced-order simulations, and to de

Robust Low-Tubal-Rank Tensor Completion under Cross-Concentrated Sampling

arXiv:2608.03928v1 Announce Type: cross Abstract: Tensor cross-concentrated sampling (t-CCS) bridges entrywise sampling and t-CUR slice-wise sampling by observing entries only within selected horizont

S^3-Diff: Structural Semantic Synergy Diffusion Model for High Fidelity Super Resolution of Pathological Images

arXiv:2608.03540v1 Announce Type: new Abstract: Digital pathology relies on high-resolution whole slide images for accurate diagnosis, yet limitations in imaging devices, storage, and transmission oft