Search: “pretraining”

Self-Evolving Harness on Multiple Tasks with the Agent as Its Own Optimizer

arXiv:2609.38372v1 Announce Type: new Abstract: A harness is the code around a language-model agent that organizes prompts, calls tools, manages context, and controls execution. As models grow stronge

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SimTrace: Grounded Multimodal User Trajectories Generation for Online User Modeling

DGX agent

arXiv:2609.38397v1 Announce Type: new Abstract: Virtual clients offer a cost-effective approach to support applications such as A/B testing, recommender system development, and interface evaluation. H

agentsarxiv-cs-ai

1 Oct 2026

StereoGaussians: Feed-Forward 3D Gaussian Splatting from Stereo Images

arXiv:2609.38592v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting (3DGS) enables reconstruction without per- scene optimisation, but practical stereo-camera applications require nearb

Systematically Exploring the Capabilities of GPT-6 Astra as Embodied Policies

arXiv:2609.38537v1 Announce Type: new Abstract: GPT-6 Astra exhibits a remarkable ability to generate numerical robot actions, extending its role beyond high-level planning. To assess Astra's capabili

local-aiarxiv-cs-ro

TED:Text-Axis Evidence Decomposition for Prompted Anomaly Localization

arXiv:2609.39033v1 Announce Type: cross Abstract: CLIP is a powerful vision-language model, but it was not designed for fine-grained defect localization; CLIP-based anomaly detectors therefore adapt i

Text-to-3D Policy: Fine-Grained Language-Behavior Alignment for Unseen Specification Generalization

arXiv:2609.39599v1 Announce Type: cross Abstract: 3D visuomotor policies provide a strong foundation for spatially precise manipulation, yet current text-to-3D policies struggle to follow unseen fine-

TexTailor: Texture-Preserving Video Virtual Try-On via Adaptive Garment Conditioning

arXiv:2609.39335v1 Announce Type: new Abstract: Video virtual try-on has attracted increasing attention due to its broad potential in digital fashion and intelligent e-commerce. However, existing meth

Two-Step Data Augmentation for Masked Face Detection and Recognition: Turning Fake Masks to Real

arXiv:2512.15774v5 Announce Type: replace Abstract: The absence of large-scale masked face datasets challenges masked face detection and recognition. We propose a two-step generative data augmentation

Validity-Preserving Hierarchical RL for Joint Routing and Switch Placement in EDA

arXiv:2609.39749v1 Announce Type: new Abstract: Routing and switch placement are fundamental combinatorial optimization problems in chip design, requiring the joint optimization of routing topology an

ViLegalExpert: A Large-Scale Benchmark for Vietnamese Legal Retrieval and Question Answering from Real-World Consultations

model-releasesarxiv-cs-cl

arXiv:2609.39189v1 Announce Type: new Abstract: Trustworthy Legal AI requires systems that can answer legal questions while grounding their responses in authoritative sources. However, existing Vietna

Agents

Vision-Language-Action Autonomous Driving Agent with Language-based Memory

arXiv:2609.38641v1 Announce Type: new Abstract: Vision-Language-Action (VLA) foundation models have recently emerged as one of the prevailing solutions for autonomous driving, as they can utilize know

agentsarxiv-cs-cv

WEIRDO: WEak resIdual Regularized DOob's h-transform diffusion alignment

arXiv:2609.39531v1 Announce Type: cross Abstract: We study the problem of estimating the guidance that steers the distribution learned by a diffusion generative model toward a tilted target q_0 propto

safetyarxiv-cs-lg

Whitening Improves Robustness to Spurious Correlations in Linear Probes

arXiv:2609.39177v1 Announce Type: new Abstract: Deep neural networks tend to rely on simple features that may be spurious and thus fail to generalize. We study this problem in the setting of linear pr

Adversarial Training for Pixel Diffusion

arXiv:2609.38170v1 Announce Type: new Abstract: Pixel diffusion models generate RGB images directly, avoiding the bottleneck of an autoencoder, yet their outputs still systematically underrepresent fi

safetyarxiv-cs-cv

Architecture Alignment With Sparse Priors in Tabular Foundation Models

model-releasesarxiv-cs-lg

arXiv:2609.36883v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are increasingly popular because they deliver strong predictions on new datasets through in-context learning, without t

AutoMark: Enabling Autoresearch to Discover Better LLM Watermarks

model-releasesarxiv-cs-lg

arXiv:2609.37310v1 Announce Type: cross Abstract: With LLM watermarking being deployed commercially and now required by regulations, improving its reliability and effectiveness has become crucial. Yet

AVIO: Learning to Add and Remove Sounding Objects in Audiovisual Scenes

arXiv:2609.36503v1 Announce Type: new Abstract: Adding or removing a sounding object requires coordinated changes to visual content and sound while preserving the surrounding scene. Yet paired supervi

local-aiarxiv-cs-ai

Backpropagated Output Momentum: Relocating Optimizer History from Parameters to Task Space

model-releasesarxiv-cs-cl

arXiv:2609.36738v1 Announce Type: cross Abstract: Optimizer momentum is usually stored as a parameter-sized moving average of past gradients, which makes history costly and fixes each past signal in t

BaLEEN: Biasing with Latent Encoded Entities for Context-Aware ASR

arXiv:2609.36913v1 Announce Type: cross Abstract: Transcribing domain-specific entities and rare proper nouns remains a major challenge in automatic speech recognition (ASR). In this paper, we propose

Beyond Semantics: How Temporal Biases Shape Retrieval in Transformer and State-Space Models

arXiv:2510.22752v2 Announce Type: replace-cross Abstract: In-context learning is governed by both temporal and semantic relationships, shaping how Large Language Models (LLMs) retrieve contextual info

CogWAM: Aligning Semantic Cognition with World Action Modeling via Event-Driven Interfaces

arXiv:2609.37721v1 Announce Type: cross Abstract: Robot policies increasingly incorporate semantic reasoning and future-world prediction, yet combining these capabilities does not guarantee that local

local-aiarxiv-cs-cv

CoRe: Co-Evolving Reward Models for Mitigating Latent Reward Hacking in Video Diffusion Models

arXiv:2609.36245v1 Announce Type: new Abstract: Latent reward models (LRMs) enable efficient alignment of video diffusion models by scoring intermediate states directly in latent space. However, we fi

CrossTimeEdit: A Decade-Spanning Cross-View Dataset and Reward-Guided Editing for Historical Street-View Generation

arXiv:2609.36616v1 Announce Type: new Abstract: Historical street-view imagery records urban evolution, but uneven coverage leaves substantial gaps in historical records. Generating plausible past app

local-aiarxiv-cs-cv

CyFA: Linear Sequence Modeling with Relative-Time-Partitioned Memory

arXiv:2609.36259v1 Announce Type: new Abstract: Linear RNNs offer linear-time sequence processing and constant-memory decoding, but their fixed-size recurrent states must accommodate all past key--val

Data Unlearning via Inverse Distillation

arXiv:2609.36099v1 Announce Type: new Abstract: Multi-step matching models, including flow and diffusion models, produce high-quality outputs but incur substantial inference costs and may reproduce un

Dyad: Extending Large Language Models with Native Typed Decision-Making

arXiv:2609.36116v1 Announce Type: new Abstract: We study how to build more capable general-purpose agents by extending large language models (LLMs) with native typed decision-making. We introduce Dyad

safetyarxiv-cs-lg

Early Learning Shapes Later Directions Of Representation Change In Continual Learning

arXiv:2609.36081v1 Announce Type: new Abstract: Representations continually change as a network learns new tasks. We ask whether early representational changes naturally form a geometric structure tha

Evaluation Choices Shape Biomedical ML Claims: A Pediatric Pneumonia Benchmark Case Study

model-releasesarxiv-cs-cv

arXiv:2609.37848v1 Announce Type: new Abstract: Biomedical machine learning papers often compress model performance into one headline number. That number can look like a property of the model even whe

Event-based Scene Synthesis via Inter-Frame Residual Alignment

arXiv:2512.17323v2 Announce Type: replace Abstract: Event-based scene synthesis reconstructs target RGB frames from sparse image observations and asynchronous event streams, encompassing both video fr

safetyarxiv-cs-cv

EviViT: Evidence-Adaptive Vision Transformers for Fine-Grained Perception

arXiv:2609.37123v1 Announce Type: new Abstract: Fine-grained visual perception enables vision-language models to distinguish subtle attributes and ground their answers in visual evidence. In high-reso

FLOORA: A Human-Aligned Domain-Specific Language Model for Architectural Design

arXiv:2609.36064v1 Announce Type: cross Abstract: Foundation models are powerful generators, but many engineering domains require structured representations that general-purpose systems handle poorly.

FocusVTC: Efficient and High-Performance Visual Text Compression with Adaptive Resolution

arXiv:2609.36651v1 Announce Type: cross Abstract: Long-context reasoning in large language models incurs substantial computation and memory costs. Visual text compression (VTC) reduces input length by

local-aiarxiv-cs-ai

GLaS-JEPA: Gaussian-Regularized Speech SSL without Engineered Prediction Targets

arXiv:2609.37798v1 Announce Type: cross Abstract: Speech self-supervised learning aims to learn general-purpose representations for downstream speech tasks. However, current approaches rely on complex

Grab a Coffee: Future-Aware Guidance for Discrete Diffusion with Compiled Objectives

arXiv:2609.35924v1 Announce Type: new Abstract: Discrete diffusion models generate sequences by iteratively resolving multiple tokens in parallel, offering a flexible alternative to left-to-right gene

researcharxiv-cs-ai

GraphVQ: Structure-Aware Autoregressive Decoding over Context-Quantized Graph Tokens

arXiv:2609.37604v1 Announce Type: new Abstract: Graph foundation models need a discrete token representation, but casting a graph as a generatable token sequence faces a structural obstacle: edges spa

How Many Labels Does a Language Need? Annotation Budgets and Cross-Lingual Pooling for African-Language Text Classification

model-releasesarxiv-cs-cl

arXiv:2609.37882v1 Announce Type: new Abstract: Every text classifier for an African language begins with a budgeting question: how many labelled examples are needed, and can labels from other African

Identifying ODEs from Unstructured Data with Causal Representation Learning

arXiv:2609.37083v1 Announce Type: cross Abstract: We study the problem of recovering the governing ODE of a dynamical system from unstructured, high-dimensional observations such as images. Existing m

researcharxiv-cs-ai

Interpretable intrinsic dimension estimation through componentwise calibration of distance and angle

arXiv:2609.37114v1 Announce Type: new Abstract: DANCo (Dimensionality from Angle and Norm Concentration) jointly calibrates nearest-neighbor distance and angular statistics and consistently reaches st

IronLLM: Forging Compact Edge-Native Language Models for Real-Time Embodied Intelligence

arXiv:2609.36860v1 Announce Type: new Abstract: We present IronLLM-0.6B, a 654M-parameter language model designed for efficient on-device inference. IronLLM-0.6B combines a hybrid attention architectu

JointEdit3D: Feed-Forward 3D Scene Editing in a Unified Latent Space

model-releasesarxiv-cs-cv

arXiv:2606.13345v2 Announce Type: replace Abstract: Existing 3D scene editing methods typically rely on per-scene optimization over explicit 3D representations or cascaded edit-and-reconstruct pipelin

Language as the Interface: Foundation-Model Contrastive Learning Links Transcriptomes and Electrophysiology

arXiv:2609.37024v1 Announce Type: new Abstract: Integrating transcriptomic and electrophysiological data is essential for building multimodal foundation models for neuroscience. Patch-seq provides pai

Med-RADIO: Reducing All Medical Domains Into One via Multi-Teacher Distillation

arXiv:2609.37682v1 Announce Type: new Abstract: The rapid expansion of large-scale medical datasets and computational resources has driven significant progress in medical foundation models. Given the

Tutorials

MemEvo: Automatic Discovery of Streaming Video Memory Mechanisms

arXiv:2609.36581v1 Announce Type: new Abstract: Query-agnostic streaming video understanding requires vision-language models to continuously compress an indefinitely growing visual stream into a bound

tutorialsarxiv-cs-ai

MoRE: Scaling mixture of experts with hardware-aware low-rank routing

arXiv:2609.36301v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) layers are central to frontier language models, and recent architectures push toward more and smaller experts. In this regime

researcharxiv-cs-ai

NIDAR: NIR-Guided Intrinsic Decomposition for Scalable Scene-Agnostic LiDAR Intensity Reconstruction

arXiv:2609.36878v1 Announce Type: new Abstract: LiDAR return intensity provides complementary surface-response cues for robotic perception and state estimation, yet many simulation pipelines omit it o

researcharxiv-cs-ro

Normalize-Then-Precondition: A Hierarchical Approach to Marginal Scale and Interaction Geometry for LLM Training

arXiv:2609.36692v1 Announce Type: cross Abstract: Matrix optimizers have emerged as a promising direction, with Muon standing out as a prominent design. Revisiting Muon through its full-Gram represent

OFBD: Object-Focused Background Debiasing for Long-Tailed Learning

arXiv:2609.37331v1 Announce Type: new Abstract: Balancing performance trade-offs on long-tailed data distributions remains a long-standing challenge in visual recognition. Existing methods mainly impr

safetyarxiv-cs-cv

On State Reduction in Linear Attention

arXiv:2602.04852v3 Announce Type: replace Abstract: Linear attention offers a computationally efficient yet expressive alternative to softmax attention. However, recent empirical results indicate that