Search: “research”

NTIRE 2026 Challenge on Video Saliency Prediction: Methods and Results

arXiv:2604.14816v1 Announce Type: new Abstract: This paper presents an overview of the NTIRE 2026 Challenge on Video Saliency Prediction. The goal of the challenge participants was to develop automati

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On the Expressive Power and Limitations of Multi-Layer SSMs

DGX agent

arXiv:2604.14501v1 Announce Type: new Abstract: We study the expressive power and limitations of multi-layer state-space models (SSMs). First, we show that multi-layer SSMs face fundamental limitation

researcharxiv-cs-lg

17 Apr 2026

One-shot Compositional 3D Head Avatars with Deformable Hair

arXiv:2604.14782v1 Announce Type: new Abstract: We propose a compositional method for constructing a complete 3D head avatar from a single image. Prior one-shot holistic approaches frequently fail to

OptEMA: Adaptive Exponential Moving Average for Stochastic Optimization with Zero-Noise Optimality

arXiv:2603.09923v3 Announce Type: replace Abstract: The Exponential Moving Average (EMA) is a cornerstone of widely used optimizers such as Adam. However, existing theoretical analyses of Adam-style m

Optimal last-iterate convergence in matrix games with bandit feedback using the log-barrier

arXiv:2604.15242v1 Announce Type: new Abstract: We study the problem of learning minimax policies in zero-sum matrix games. Fiegel et al. (2025) recently showed that achieving last-iterate convergence

OVT-MLCS: An Online Visual Tool for MLCS Mining from Long or Big Sequences

arXiv:2604.13037v1 Announce Type: cross Abstract: Mining multiple longest common subsequences (extit{MLCS}) from a set of sequences of three or more over a finite alphabet Sigma (a classical NP-hard p

Path-Sampled Integrated Gradients

arXiv:2604.14338v1 Announce Type: new Abstract: We introduce path-sampled integrated gradients (PS-IG), a framework that generalizes feature attribution by computing the expected value over baselines

Physics-Informed Machine Learning for Pouch Cell Temperature Estimation

arXiv:2604.14566v1 Announce Type: new Abstract: Accurate temperature estimation of pouch cells with indirect liquid cooling is essential for optimizing battery thermal management systems for transport

PixelDiT: Pixel Diffusion Transformers for Image Generation

arXiv:2511.20645v2 Announce Type: replace Abstract: Latent-space modeling has been the standard for Diffusion Transformers (DiTs). However, it relies on a two-stage pipeline where the pretrained autoe

Polyformer: a generative framework for thermodynamic modeling of polymeric molecules

arXiv:2604.14241v1 Announce Type: cross Abstract: The classic paradigm of structural biology is that the sequence of a biomolecule (protein, nucleic acid, lipid, etc) determines its conformation (shap

Portfolio Optimization Proxies under Label Scarcity and Regime Shifts via Bayesian and Deterministic Students under Semi-Supervised Sandwich Training

arXiv:2604.14206v1 Announce Type: new Abstract: This paper proposes a machine learning assisted portfolio optimization framework designed for low data environments and regime uncertainty. We construct

Predicting Post-Traumatic Epilepsy from Clinical Records using Large Language Model Embeddings

arXiv:2604.14547v1 Announce Type: new Abstract: Objective: Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic brain injury (TBI). Early prediction of P

Psychological Steering of Large Language Models

arXiv:2604.14463v1 Announce Type: new Abstract: Large language models (LLMs) emulate a consistent human-like behavior that can be shaped through activation-level interventions. This paradigm is conver

PUFFIN: Protein Unit Discovery with Functional Supervision

arXiv:2604.14796v1 Announce Type: cross Abstract: Proteins carry out biological functions through the coordinated action of groups of residues organized into structural arrangements. These arrangement

Q-MambaIR: Accurate Quantized Mamba for Efficient Image Restoration

arXiv:2503.21970v3 Announce Type: replace Abstract: State-Space Models (SSMs) have attracted considerable attention in Image Restoration (IR) due to their ability to scale linearly sequence length whi

QualiaNet: An Experience-Before-Inference Network

arXiv:2604.14193v1 Announce Type: new Abstract: Human 3D vision involves two distinct stages: an Experience Module, where stereo depth is extracted relative to fixation, and an Inference Module, where

Quantitative Approximation Rates for Group Equivariant Learning

arXiv:2602.20370v2 Announce Type: replace Abstract: The universal approximation theorem establishes that neural networks can approximate any continuous function on a compact set. Later works in approx

Quantization of Spiking Neural Networks Beyond Accuracy

arXiv:2604.14487v1 Announce Type: new Abstract: Quantization is a natural complement to the sparse, event-driven computation of Spiking Neural Networks, reducing memory bandwidth and arithmetic cost f

Quantum-inspired tensor networks in machine learning models

arXiv:2604.14287v1 Announce Type: new Abstract: Tensor networks were developed in the context of many-body physics as compressed representations of multiparticle quantum states. These representations

RACER: Retrieval-Augmented Contextual Rapid Speculative Decoding

arXiv:2604.14885v1 Announce Type: new Abstract: Autoregressive decoding in Large Language Models (LLMs) generates one token per step, causing high inference latency. Speculative decoding (SD) mitigate

Random Matrix Theory for Deep Learning: Beyond Eigenvalues of Linear Models

arXiv:2506.13139v2 Announce Type: replace-cross Abstract: Modern Machine Learning (ML) and Deep Neural Networks (DNNs) often operate on high-dimensional data and rely on overparameterized models, wher

ReasonScaffold: A Scaffolded Reasoning-based Annotation Protocol for Human-AI Co-Annotation

arXiv:2603.21094v3 Announce Type: replace Abstract: Human annotation is central to NLP evaluation, yet subjective tasks often exhibit substantial variability across annotators. While large language mo

Rethinking LLM-Driven Heuristic Design: Generating Efficient and Specialized Solvers via Dynamics-Aware Optimization

arXiv:2601.20868v2 Announce Type: replace Abstract: Large Language Models (LLMs) have advanced the field of Combinatorial Optimization through automated heuristic generation. Instead of relying on man

Revisiting Token Compression for Accelerating ViT-based Sparse Multi-View 3D Object Detectors

arXiv:2604.14563v1 Announce Type: new Abstract: Vision Transformer (ViT)-based sparse multi-view 3D object detectors have achieved remarkable accuracy but still suffer from high inference latency due

Robustness of Vision Foundation Models to Common Perturbations

arXiv:2604.14973v1 Announce Type: cross Abstract: A vision foundation model outputs an embedding vector for an image, which can be affected by common editing operations (e.g., JPEG compression, bright

Sandwich: Joint Configuration Search and Hot-Switching for Efficient CPU LLM Serving

arXiv:2507.18454v2 Announce Type: replace-cross Abstract: CPUs are critical for LLM serving due to their availability, cost efficiency, and edge applicability. However, efficient CPU serving is hinder

Scalable Model-Based Clustering with Sequential Monte Carlo

arXiv:2604.14810v1 Announce Type: cross Abstract: In online clustering problems, there is often a large amount of uncertainty over possible cluster assignments that cannot be resolved until more data

Agents

SciFi: A Safe, Lightweight, User-Friendly, and Fully Autonomous Agentic AI Workflow for Scientific Applications

arXiv:2604.13180v1 Announce Type: new Abstract: Recent advances in agentic AI have enabled increasingly autonomous workflows, but existing systems still face substantial challenges in achieving reliab

agentsarxiv-cs-ai

Seen-to-Scene: Keep the Seen, Generate the Unseen for Video Outpainting

arXiv:2604.14648v1 Announce Type: new Abstract: Video outpainting aims to expand the visible content of a video beyond the original frame boundaries while preserving spatial fidelity and temporal cohe

Segment-Level Coherence for Robust Harmful Intent Probing in LLMs

arXiv:2604.14865v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly exposed to adaptive jailbreaking, particularly in high-stakes Chemical, Biological, Radiological, and Nucl

SegviGen: Repurposing 3D Generative Model for Part Segmentation

arXiv:2603.16869v2 Announce Type: replace Abstract: We introduce SegviGen, a framework that repurposes native 3D generative models for 3D part segmentation. Existing pipelines either lift strong 2D pr

SegWithU: Uncertainty as Perturbation Energy for Single-Forward-Pass Risk-Aware Medical Image Segmentation

arXiv:2604.15271v1 Announce Type: new Abstract: Reliable uncertainty estimation is critical for medical image segmentation, where automated contours feed downstream quantification and clinical decisio

Similarity-Distance-Magnitude Activations

arXiv:2509.12760v4 Announce Type: replace-cross Abstract: We introduce the Similarity-Distance-Magnitude (SDM) activation function, a more robust and interpretable formulation of the standard softmax

SPaCe: Unlocking Sample-Efficient Large Language Models Training With Self-Pace Curriculum Learning

arXiv:2508.05015v2 Announce Type: replace Abstract: Large language models (LLMs) have shown strong reasoning capabilities when fine-tuned with reinforcement learning (RL). However, such methods requir

Stability and Generalization in Looped Transformers

arXiv:2604.15259v1 Announce Type: new Abstract: Looped transformers promise test-time compute scaling by spending more iterations on harder problems, but it remains unclear which architectural choices

STEP-Parts: Geometric Partitioning of Boundary Representations for Large-Scale CAD Processing

arXiv:2604.14927v1 Announce Type: cross Abstract: Many CAD learning pipelines discretize Boundary Representations (B-Reps) into triangle meshes, discarding analytic surface structure and topological a

StreamCacheVGGT: Streaming Visual Geometry Transformers with Robust Scoring and Hybrid Cache Compression

arXiv:2604.15237v1 Announce Type: new Abstract: Reconstructing dense 3D geometry from continuous video streams requires stable inference under a constant memory budget. Existing O(1) frameworks primar

Structural interpretability in SVMs with truncated orthogonal polynomial kernels

arXiv:2604.15285v1 Announce Type: cross Abstract: We study post-training interpretability for Support Vector Machines (SVMs) built from truncated orthogonal polynomial kernels. Since the associated re

Structure as Computation: Developmental Generation of Minimal Neural Circuits

arXiv:2604.15143v1 Announce Type: cross Abstract: This work simulates the developmental process of cortical neurogenesis, initiating from a single stem cell and governed by gene regulatory rules deriv

Style Amnesia: Investigating Speaking Style Degradation and Mitigation in Multi-Turn Spoken Language Models

arXiv:2512.23578v3 Announce Type: replace Abstract: In this paper, we show that when spoken language models (SLMs) are instructed to speak in a specific speaking style at the beginning of a multi-turn

The Code Whisperer: LLM and Graph-Based AI for Smell and Vulnerability Resolution

arXiv:2604.13114v1 Announce Type: cross Abstract: Code smells and software vulnerabilities both increase maintenance cost, yet they are often handled by separate tools that miss structural context and

The Cognitive Circuit Breaker: A Systems Engineering Framework for Intrinsic AI Reliability

arXiv:2604.13417v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly deployed in mission-critical software systems, detecting hallucinations and ``faked truthfulness'' ha

Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling

arXiv:2601.12145v2 Announce Type: replace Abstract: Softmax attention struggles with long contexts due to structural limitations: the strict sum-to-one constraint forces attention sinks on irrelevant

Tight Bounds for Learning Polyhedra with a Margin

arXiv:2604.14614v1 Announce Type: cross Abstract: We give an algorithm for PAC learning intersections of k halfspaces with a rho margin to within error arepsilon that runs in time extsf{poly}(k, areps

TokenFormer: Unify the Multi-Field and Sequential Recommendation Worlds

arXiv:2604.13737v1 Announce Type: cross Abstract: Recommender systems have historically developed along two largely independent paradigms: feature interaction models for modeling correlations among mu

TokenGS: Decoupling 3D Gaussian Prediction from Pixels with Learnable Tokens

arXiv:2604.15239v1 Announce Type: new Abstract: In this work, we revisit several key design choices of modern Transformer-based approaches for feed-forward 3D Gaussian Splatting (3DGS) prediction. We

TokenLight: Precise Lighting Control in Images using Attribute Tokens

arXiv:2604.15310v1 Announce Type: new Abstract: This paper presents a method for image relighting that enables precise and continuous control over multiple illumination attributes in a photograph. We

Towards Design Compositing

arXiv:2604.14605v1 Announce Type: new Abstract: Graphic design creation involves harmoniously assembling multimodal components such as images, text, logos, and other visual assets collected from diver