Search: “framework”

Teacher-Feature Drifting: One-Step Diffusion Distillation with Pretrained Diffusion Representations

arXiv:2605.07327v1 Announce Type: new Abstract: Sampling from pretrained diffusion and flow-matching models typically requires many forward passes to generate diverse and high-fidelity images. Existin

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Teaching Language Models to Think in Code

DGX agent

arXiv:2605.07237v1 Announce Type: new Abstract: Tool-integrated reasoning (TIR) has emerged as a dominant paradigm for mathematical problem solving in language models, combining natural language (NL)

model-releasesarxiv-cs-cl

11 May 2026

Temporal Attention for Adaptive Control of Euler-Lagrange Systems with Unobservable Memory

arXiv:2605.06877v1 Announce Type: new Abstract: Adaptive control of Euler-Lagrange systems is challenging when friction is governed by a finite-horizon internal state that is not directly observable f

safetyarxiv-cs-lg

Temporal Smoothness Doubly Robust Learning for Debiased Knowledge Tracing

arXiv:2605.05958v2 Announce Type: replace Abstract: Knowledge Tracing (KT) is fundamental to intelligent education systems, yet relies on educational logs that are selectively observed. The non-random

Testing Noise Assumptions of Learning Algorithms

arXiv:2501.09189v3 Announce Type: replace Abstract: We pose a fundamental question in computational learning theory: can we efficiently test whether a training set satisfies the assumptions of a given

researcharxiv-cs-lg

TextLDM: Language Modeling with Continuous Latent Diffusion

arXiv:2605.07748v1 Announce Type: new Abstract: Diffusion Transformers (DiT) trained with flow matching in a VAE latent space have unified visual generation across images and videos. A natural next st

The Effect of Mini-Batch Noise on the Implicit Bias of Adam

arXiv:2602.01642v2 Announce Type: replace-cross Abstract: With limited high-quality data and growing compute, multi-epoch training is gaining back its importance across sub-areas of deep learning. Ada

The Endogeneity of Miscalibration: Impossibility and Escape in Scored Reporting

arXiv:2605.07671v1 Announce Type: cross Abstract: Eliciting truthful reports from autonomous agents is a core problem in scalable AI oversight: a principal scores the agent's report using a strictly p

Local Ai

Think Before You Drive: World Model-Inspired Multimodal Grounding for Autonomous Vehicles

arXiv:2512.03454v4 Announce Type: replace-cross Abstract: Interpreting natural-language commands to localize target objects is critical for autonomous driving (AD). Existing visual grounding (VG) meth

local-aiarxiv-cs-ai

Think-with-Rubrics: From External Evaluator to Internal Reasoning Guidance

arXiv:2605.07461v1 Announce Type: new Abstract: Rubrics have been extensively utilized for evaluating unverifiable, open-ended tasks, with recent research incorporating them into reward systems for re

THINKSAFE: Self-Generated Safety Alignment for Reasoning Models

arXiv:2601.23143v2 Announce Type: replace Abstract: Large reasoning models (LRMs) achieve remarkable performance by leveraging reinforcement learning (RL) on reasoning tasks to generate long chain-of-

ThinKV: Thought-Adaptive KV Cache Compression for Efficient Reasoning Models

model-releasesarxiv-cs-lg

arXiv:2510.01290v2 Announce Type: replace Abstract: The long-output context generation of large reasoning models enables extended chain of thought (CoT) but also drives rapid growth of the key-value (

Three-in-One World Model: Energy-Based Consistency, Prediction, and Counterfactual Inference for Marketing Intervention

arXiv:2605.07199v1 Announce Type: new Abstract: Marketing decisions reflect the interaction of latent consumer heterogeneity, time-varying internal states, and explicit interventions, a structure that

TimeLesSeg: Unified Contrast-Agnostic Cross-Sectional and Longitudinal MS Lesion Segmentation via a Stochastic Generative Model

arXiv:2605.07955v1 Announce Type: cross Abstract: Multiple sclerosis (MS) expresses substantial clinical and radiological heterogeneity, which poses significant challenges for automatic lesion segment

Local Ai

Topology-Enhanced Alignment for Large Language Models: Trajectory Topology Loss and Topological Preference Optimization

arXiv:2605.07172v1 Announce Type: new Abstract: Alignment of large language models (LLMs) via SFT and RLHF/DPO typically ignores the global geometry of the representation space, relying instead on loc

local-aiarxiv-cs-cl

Toward Better Geometric Representations for Molecule Generative Models

arXiv:2605.07693v1 Announce Type: new Abstract: Geometric representation-conditioned molecule generation provides an effective paradigm that decouples molecule representation modeling from structure g

safetyarxiv-cs-lg

Toward Privileged Foundation Models:LUPI for Accelerated and Improved Learning

arXiv:2605.07799v1 Announce Type: cross Abstract: Training foundation models is computationally intensive and often slow to converge.We introduce PIQL,Privileged Information for Quick and Quality Lear

Agents

Towards Autonomous Business Intelligence via Data-to-Insight Discovery Agent

arXiv:2605.07202v1 Announce Type: new Abstract: Transforming fragmented enterprise data into actionable insights remains a significant challenge for LLMs, constrained by complex database schemas, limi

agentsarxiv-cs-ai

Towards Explainable Industrial Anomaly Detection via Knowledge-Guided Latent Reasoning

arXiv:2602.09850v2 Announce Type: replace Abstract: Industrial anomaly detection demands precise reasoning over fine-grained defect patterns. However, existing multimodal large language models (MLLMs)

Towards Fairness under Label Bias in Image Segmentation: Impact, Measurement and Mitigation

arXiv:2605.06891v1 Announce Type: new Abstract: Labeled datasets reflect the biases of their annotation pipelines, which sometimes introduce label bias: group-conditional label errors that cause syste

safetyarxiv-cs-cv

TRACE: Transport Alignment Conformal Prediction via Diffusion and Flow Matching Models

arXiv:2605.07100v1 Announce Type: cross Abstract: Constructing valid and informative conformal prediction regions for multi-dimensional outputs remains a fundamental challenge. While conformal predict

safetyarxiv-cs-lg

Local Ai

Tracking Large-scale Shared Bikes with Inertial Motion Learning in GNSS Blocked Environments

arXiv:2605.07412v1 Announce Type: cross Abstract: Although Global Navigation Satellite Systems (GNSS) provide a general solution for bike tracking outdoors, there still exist complex riding environmen

local-aiarxiv-cs-ai

Training-Free Multimodal Large Language Model Orchestration

arXiv:2508.10016v3 Announce Type: replace Abstract: Building interactive omni-modal assistants often relies on end-to-end multimodal alignment to fuse heterogeneous modalities, which incurs substantia

TriP: A Triangle Puzzle Approach to Robust Translation Averaging

arXiv:2605.07143v1 Announce Type: new Abstract: Translation averaging aims to recover camera locations from pairwise relative translation directions and is a fundamental component of global Structure-

TTF: Temporal Token Fusion for Efficient Video-Language Model

arXiv:2605.07355v1 Announce Type: cross Abstract: Video-language models (VLMs) face rapid inference costs as visual token counts scale with video length. For example, 32 frames at 448{imes}448 resolut

UFT: Unifying Fine-Tuning of SFT and RLHF/DPO/UNA through a Generalized Implicit Reward Function

arXiv:2410.21438v3 Announce Type: replace Abstract: By pretraining on trillions of tokens, an LLM gains the capability of text generation. However, to enhance its utility and reduce potential harm, SF

Uncertainty-Aware Structured Data Extraction from Full CMR Reports via Distilled LLMs

arXiv:2605.08045v1 Announce Type: new Abstract: Converting free-text cardiac magnetic resonance (CMR) reports into auditable structured data remains a bottleneck for cohort assembly, longitudinal cura

researcharxiv-cs-cl

Uncertainty Quantification for Cardiac Shape Reconstruction with Deep Signed Distance Functions via MCMC methods

arXiv:2605.07987v1 Announce Type: cross Abstract: Atlas-based approaches allow high-quality, patient-specific shape reconstructions of cardiac anatomy from sparse and/or noisy data such as point cloud

Uncovering Hidden Systematics in Neural Network Models for High Energy Physics

arXiv:2605.07470v1 Announce Type: new Abstract: Neural networks (NNs) are inherently multidimensional classifiers that learn complex, non-linear relationships among input observables. While their flex

tutorialsarxiv-cs-lg

Uneven Evolution of Cognition Across Generations of Generative AI Models

arXiv:2605.06815v1 Announce Type: new Abstract: The pursuit of artificial general intelligence necessitates robust methods for evaluating the cognitive capabilities of models beyond narrow task perfor

UniD-Shift: Towards Unified Semantic Segmentation via Interpretable Share-Private Multimodal Decomposition

arXiv:2605.07356v1 Announce Type: new Abstract: Semantic segmentation of large-scale 3D point clouds is crucial for applications such as autonomous driving and urban digital twins. However, the sparse

safetyarxiv-cs-cv

UniV2D: Bridging Visual Restoration and Semantic Perception for Underwater Salient Object Detection

arXiv:2605.07146v1 Announce Type: new Abstract: Underwater salient object detection (USOD) plays a vital role in marine vision tasks but remains fundamentally challenging due to severe visual degradat

tutorialsarxiv-cs-cv

Unsolvability Ceiling in Multi-LLM Routing: An Empirical Study of Evaluation Artifacts

arXiv:2605.07395v1 Announce Type: cross Abstract: Efficient routing across multiple LLMs enables cost-quality tradeoffs by directing queries to the cheapest capable model. Prior work attributes routin

Upper Generalization Bounds for Neural Oscillators

arXiv:2603.09742v2 Announce Type: replace Abstract: Neural oscillators that originate from second-order ordinary differential equations (ODEs) have shown competitive performance in learning mappings b

researcharxiv-cs-lg

VDEGaussian: Video Diffusion Enhanced 4D Gaussian Splatting for Dynamic Urban Scenes Modeling

arXiv:2508.02129v2 Announce Type: replace Abstract: Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gauss

safetyarxiv-cs-cv

VecCISC: Improving Confidence-Informed Self-Consistency with Reasoning Trace Clustering and Candidate Answer Selection

arXiv:2605.08070v1 Announce Type: new Abstract: A standard technique for scaling inference-time reasoning is Self-Consistency, whereby multiple candidate answers are sampled from an LLM and the most c

Velocity-Space 3D Asset Editing

arXiv:2605.07385v1 Announce Type: cross Abstract: Editing a 3D asset locally, modifying a target region while preserving the rest, is a fundamental requirement of native 3D editing. Existing methods e

VesselRW: Weakly Supervised Subcutaneous Vessel Segmentation via Learned Random Walk Propagation

arXiv:2508.06819v3 Announce Type: replace Abstract: The task of parsing subcutaneous vessels in clinical images is often hindered by the high cost and limited availability of ground truth data, as wel

tutorialsarxiv-cs-cv

Video Understanding Reward Modeling: A Robust Benchmark and Performant Reward Models

arXiv:2605.07872v1 Announce Type: cross Abstract: Multimodal reward models have advanced substantially in text and image domains, yet progress in video understanding reward modeling remains severely l

VideoRouter: Query-Adaptive Dual Routing for Efficient Long-Video Understanding

arXiv:2605.05848v2 Announce Type: replace-cross Abstract: Video large multimodal models increasingly face a scalability bottleneck: long videos produce excessively long visual-token sequences, which s

VISD: Enhancing Video Reasoning via Structured Self-Distillation

arXiv:2605.06094v2 Announce Type: replace-cross Abstract: Training VideoLLMs for complex reasoning remains challenging due to sparse sequence level rewards and the lack of fine grained credit assignme

VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts

model-releasesarxiv-cs-ro

arXiv:2605.06175v2 Announce Type: replace Abstract: Vision-language-action (VLA) models inherit rich visual-semantic priors from pre-trained vision-language backbones, but adapting them to robotic con

Agents

WebClipper: Efficient Evolution of Web Agents with Graph-based Trajectory Pruning

arXiv:2602.12852v2 Announce Type: replace Abstract: Deep Research systems based on web agents have shown strong potential in solving complex information-seeking tasks, yet their search efficiency rema

agentsarxiv-cs-ai

Agents

When Stored Evidence Stops Being Usable: Scale-Conditioned Evaluation of Agent Memory

arXiv:2605.07313v1 Announce Type: new Abstract: Memory-agent evaluations report fixed-snapshot accuracy or retrieval quality, but these scores do not show whether evidence remains usable as irrelevant

agentsarxiv-cs-ai

When Symbol Names Should Not Matter: A Logistic Theory of Fresh-Symbol Classification

arXiv:2605.07120v1 Announce Type: new Abstract: Template tasks have emerged as a clean testbed for asking whether transformers reason with abstract symbols rather than concrete token names. We study t

tutorialsarxiv-cs-lg

Who Prices Cognitive Labor in the Age of Agents? Compute-Anchored Wages

arXiv:2605.05558v2 Announce Type: replace Abstract: A natural intuition about the economics of AI agents is that, because agents can be replicated at very low marginal cost, agent labor may be supplie

Why Self-Inconsistency Arises in GNN Explanations and How to Exploit It

arXiv:2605.07527v1 Announce Type: cross Abstract: Recent work has observed that explanations produced by Self-Interpretable Graph Neural Networks (SI-GNNs) can be self-inconsistent: when the model is

WorldCup Sampling for Multi-bit LLM Watermarking

arXiv:2602.01752v2 Announce Type: replace Abstract: As large language models (LLMs) generate increasingly human-like text, watermarking has emerged as a promising solution for reliable attribution bey

researcharxiv-cs-cl