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Adaptive Test-Time Compute Allocation for Block Diffusion Language Models in Complex Reasoning

arXiv:2602.09555v3 Announce Type: replace Abstract: Recent advances in block diffusion language models have demonstrated competitive performance and strong scalability on reasoning tasks. However, the

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AdaR: A Framework for Equipping LLMs with Adaptive Reasoning

DGX agent

arXiv:2510.04617v3 Announce Type: replace Abstract: Mathematical reasoning is a primary indicator of large language models (LLMs) intelligence. However, existing LLMs exhibit failures in robustness an

researcharxiv-cs-ai

25 Aug 2026

AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies

arXiv:2501.16760v2 Announce Type: replace Abstract: Automated interpretation of seismic images using deep learning methods is challenging because of the limited availability of training data. Few-shot

ADDA: a Modular Framework for Representing, Simulating and Assimilating Dynamics with End-to-end Differentiability

arXiv:2608.23297v1 Announce Type: cross Abstract: Data assimilation (DA) is an essential tool for prediction and understanding in the geosciences. DA combines simulation programs representing scientif

ADMIL: Attention-Distilled Multiple Instance Learning for Selective Foundation Model Inference in Pathology

arXiv:2608.22066v1 Announce Type: cross Abstract: Attention-based multiple instance learning (ABMIL) using pathology foundation model embeddings is effective for slide-level tasks, but exhaustive infe

Advanced LLM-Enhanced Intent-Based 5G Network Management using Dynamic Semantic Routes

arXiv:2608.22644v1 Announce Type: cross Abstract: As the use of Artificial Intelligence (AI) and Large Language Models (LLMs) is becoming common in everyday applications, their ability to interpret na

Adversarial Robustness of Phishing Email Detection: A Comparative Study of TF-IDF + Logistic Regression and Fine-Tuned DistilBERT

arXiv:2607.18429v2 Announce Type: replace-cross Abstract: Phishing emails remain one of the most persistent cybersecurity threats, and machine-learning classifiers are widely used to detect them. Most

AI emotional support is better only when chosen, but shifts preferences even when it is not

arXiv:2608.23196v1 Announce Type: new Abstract: People increasingly face a novel decision when seeking emotional support: human or AI. In existing studies, AI's empathic messages are rated as well as

AI Learning and Conceptual Transfer in the Game of Hidden Rules

arXiv:2608.21372v1 Announce Type: new Abstract: This report summarizes the work conducted on the Game of Hidden Rules (GOHR), focusing on reinforcement learning agents trained to infer hidden rules fr

All four leading LLMs talk more than they listen to personality-verified synthetic help-seekers

arXiv:2608.22425v1 Announce Type: cross Abstract: Large language models are increasingly consulted at moments of distress, yet single-turn benchmarks neither test sustained exchanges nor distinguish b

An Interpretable Deep Learning Framework for Material Perception and Classification from Multisensory Tactile Data

arXiv:2608.21894v1 Announce Type: new Abstract: Human tactile perception relies on complex multisensory cues. Yet the relationship between tactile signals and perceptual representations remains poorly

researcharxiv-cs-ro

AquaFlow: A Monocular Gaussian Splatting SLAM for Underwater Streaming Reconstruction

arXiv:2608.22906v1 Announce Type: new Abstract: Recent monocular 3D Gaussian Splatting (3DGS) streaming reconstruction methods have achieved impressive performance by balancing reconstruction quality

Arbitrarily Shaped Scene Text Detection: A Decade of Advances and Systematic Analysis

arXiv:2107.11800v2 Announce Type: replace Abstract: Scene text detection has become an important research area in computer vision. However, dynamic changes in scenes and the complex diversity of text

ARCHER: Amortized cross-specimen pose estimation for cryo-electron microscopy

arXiv:2608.22029v1 Announce Type: new Abstract: Single-particle cryo-electron microscopy (cryo-EM) pose estimation is traditionally solved anew for each dataset, where iterative refinement is done fro

As-Rigid-As-Possible Regularization for Implicit Surfaces

arXiv:2608.15933v1 Announce Type: cross Abstract: Implicit surface representations have regained popularity because of their use in machine learning. A common component in optimization is regularizati

Ask or Answer: A Decision Framework for Multi-Turn Health Misinformation Intervention

arXiv:2608.21721v1 Announce Type: new Abstract: Correcting health misinformation in dialogue requires more than producing a factual rebuttal: users differ in what they know, what they believe, and wha

AudioNoisePrints: Model-free audio watermarking using spatial correlation in flow matching TTS

arXiv:2608.22186v1 Announce Type: cross Abstract: We present AudioNoisePrints, a training-free watermarking pipeline for flow matching and diffusion TTS models, which requires minimal extra computatio

Automating Multi-Hop RAG Evaluation via TRIAD: From Context Extraction to Validated Dataset Generation

arXiv:2608.21558v1 Announce Type: cross Abstract: Recent advances in LLMs and the adoption of RAG systems in industry have created a need for domain-specific question-answer datasets that can assess R

BC-IHV: Conditioning the Color Space for Stable Rectified-Flow Low-Light Enhancement

arXiv:2608.21847v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) must correct ambiguous exposure without overwriting structure already supported by the input. Generative transport ca

Benchmarking Retrieval-Augmented Generation Strategies for Large Language Model-Based Travel Mode Choice Prediction

arXiv:2508.17527v2 Announce Type: replace Abstract: Accurately predicting travel mode choice is essential for effective transportation planning, yet traditional statistical and machine learning models

BenthicDINO: Physics-Informed Self-Distillation for View-Invariant Side-Scan Sonar Representations

arXiv:2608.23215v1 Announce Type: cross Abstract: Automated perception in side-scan sonar (SSS) imagery is severely hindered by physical acoustic artifacts, resulting in representations that inextrica

BenthicFlow: Generating Extensible Underwater Environments via Flow Matching

arXiv:2608.23173v1 Announce Type: new Abstract: Computer vision applications for 3D scene understanding in underwater environments remain challenging due to the lack of high-quality 3D data and the in

Better Retrieval, Worse Robustness:How Multi-hop RAG Amplifies Upstream ASR Errors

arXiv:2608.22872v1 Announce Type: new Abstract: Speech-based applications pass spoken queries through automatic speech recognition (ASR) before any retrieval module, so ASR errors enter the pipeline a

Beyond chlorophyll: machine learning estimates of diagnostic phytoplankton pigments from multispectral ocean colour data

arXiv:2608.23348v1 Announce Type: cross Abstract: Phytoplankton play a central role in marine ecosystems and the global carbon cycle, with different groups contributing differently to ocean biogeochem

Beyond Fixed Directions: Adaptive Representation Analysis of Reasoning and Memorization in LLMs

arXiv:2608.21919v1 Announce Type: new Abstract: Recent work has proposed that reasoning and memorization in language models can be characterized by a single representation direction, including methods

Beyond Instance Slots: Semantically Rich World Models for Physical Interaction Planning

arXiv:2608.22294v1 Announce Type: new Abstract: World models for physical interaction are typically trained to predict future observations or latent features; however, a planning-oriented model must a

researcharxiv-cs-ro

Beyond Observed Auxiliary Relations: Environment-Conditioned Modeling for Multi-Behavior Recommendation

arXiv:2608.22920v1 Announce Type: new Abstract: Multi-behavior recommendation (MBR) leverages auxiliary behavioral signals, such as clicks and add-to-cart, to enhance target behavior prediction like p

Beyond Similarity: Heterogeneous Graph Learning for Multi-Objective Food Substitution in Charitable Food Agencies

arXiv:2608.21979v1 Announce Type: new Abstract: Charitable food agencies play an important role in alleviating food insecurity by distributing donated food to people in need. However, they rely on ad

Bidding-Aware Retrieval for Multi-Stage Consistency in Online Advertising

arXiv:2508.05206v2 Announce Type: replace Abstract: Online advertising systems typically use a cascaded architecture to manage massive requests and candidate volumes, where the ranking stages allocate

Boosting Knowledge-based Visual Question Answering with Structured Context Reasoning

arXiv:2608.21431v1 Announce Type: new Abstract: Knowledge-based Visual Question Answering aims to answer questions about an image by integrating external knowledge with visual and textual information.

Bridge Damage Detection from Low-Light UAV Imagery via Degradation-Aware Mixture-of-Experts Enhancement

arXiv:2608.23136v1 Announce Type: new Abstract: Poor illumination obscures small, low-contrast defects in UAV bridge imagery, reducing the reliability and operational flexibility of automated inspecti

Can Large Language Models 'Hyper-Thread'?

arXiv:2608.22376v1 Announce Type: new Abstract: Large language models generate tokens sequentially, but can they execute multiple tasks concurrently while forming each token? Broader attention allocat

CaRGo-T: Causal Reasoning Graph-of-Thought improves Multimodal Humor Comprehension

arXiv:2608.23172v1 Announce Type: new Abstract: Large-scale vision-language models (VLMs) have demonstrated remarkable versatility across a wide range of multimodal tasks. However, understanding humor

ChainPrune: Evaluating and Reducing Redundancy in Long Chain-of-Thought Reasoning

arXiv:2608.21860v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) reasoning has significantly enhanced the multi-step problem-solving capabilities of large language models (LLMs) by introducing

Change Detection in Probability Flow ODE: Online Testing in Diffusion Latent Spaces

arXiv:2608.22807v1 Announce Type: new Abstract: A rapidly growing range of sequential data tasks, such as identifying trend reversals in financial markets, auto-segmenting video and audio recordings,

Characterizing Necessary Losers to Explain Tournaments Losers

arXiv:2608.23446v1 Announce Type: new Abstract: We study the problem of formally explaining why a candidate was not selected by a given tournament rule, by identifying sub-tournaments in which the can

ChebBooster: A Training-Free Approach for Efficient Diffusion Transformer Inference via Chebyshev-Inspired Extrapolation

arXiv:2608.23429v1 Announce Type: cross Abstract: Diffusion Transformers (DiTs) have shown strong performance in high-fidelity image generation, but their sampling process remains computationally inte

Class-Conditioned Gaussian Mixture Modeling for Imbalanced Time Series Quantification

arXiv:2608.21473v1 Announce Type: new Abstract: Quantification, estimating class prevalences in bags of unlabeled instances is vital in domains where aggregate statistics are more important than indiv

Clinically Grounded Privacy Evaluation of Medical LMs

arXiv:2606.09590v2 Announce Type: replace Abstract: Medical language models (LMs) can memorize and reproduce protected health information, but privacy evaluations often focus on recovery of training t

Close Shortcut Wins Long: Seeking Diverse and Stable Generators for Data-Free Knowledge Distillation

arXiv:2608.22003v1 Announce Type: new Abstract: Data-Free Knowledge Distillation (DFKD) preserves privacy by transferring knowledge without real data access. However, existing generator-based DFKD met

Closed-Loop Bayesian Molecular Inverse Design with Semantic LLM Surrogates

arXiv:2608.22967v1 Announce Type: new Abstract: Practical molecular inverse design is rarely a one-shot generation problem; it often takes the form of closed-loop candidate-pool enrichment, where unde

Closing the Curvature Gap: Full Transformer Hessians

arXiv:2510.16927v2 Announce Type: replace Abstract: The optimization landscape of Transformer models remains poorly understood despite their widespread adoption. While recent studies have derived curv

CLSC DETR: Reliable Candidate Ranking via Cross Layer Geometric Support for UAV Small Object Detection

arXiv:2608.21457v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) object detection is critical for applications such as target search, where accurate detection of small objects in complex

Coarse Indexing, Fine Evidence: Decoupling Temporal Granularity in Long-Video RAG

arXiv:2608.23011v1 Announce Type: cross Abstract: Graph-based retrieval-augmented generation (RAG) provides a scalable paradigm for long-video understanding, but existing systems typically inherit a f

Cognitive Profiling of LRMs' Reasoning Traces Using Bloom's Taxonomy

arXiv:2608.23205v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) have revolutionized reasoning in LLMs, and the increasing public availability of reasoning traces creates valuable opportu

Competitive Memory Readout for Robust Video Object Segmentation: 2nd Place Technical Report for the MOSEv2 Track of the 8th LSVOS Challenge

arXiv:2608.22064v1 Announce Type: new Abstract: We present our solution for the MOSEv2 track of the 8th Large-scale Video Object Segmentation (LSVOS) Challenge at ECCV 2026. The challenge evaluates ro

Complexity Induction: Compositional Generalization via Structured Label Distortion

arXiv:2608.21464v1 Announce Type: cross Abstract: We demonstrate that structured distortion of training data - which we term complexity induction - can induce compositional generalization in a standar

Conditional regression for the Nonlinear Single-Variable Model

arXiv:2411.09686v4 Announce Type: replace-cross Abstract: Regressing a function F on R^d without incurring the statistical and computational curse of dimensionality requires exploitable structure. Com