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arXiv:2607.00865v1 Announce Type: new Abstract: Bayesian Optimisation (BO) under unknown constraints is particularly challenging when feasible regions are small. In such settings, existing methods tha

applicationsarxiv-cs-lg

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Continual learning is probably the biggest barrier to explosive AI adoption (& may have big implications for recursive self-improvement as w…

DGX agent

Continual learning is probably the biggest barrier to explosive AI adoption (& may have big implications for recursive self-improvement as well) As long as you deal with amnesiac models that require h

model-releasesethan-mollick--x

2 Jul 2026

Crystalite: A Lightweight Transformer for Efficient Crystal Modeling

arXiv:2604.02270v2 Announce Type: replace-cross Abstract: Generative models for crystalline materials often rely on equivariant graph neural networks, which capture geometric structure well but are co

researcharxiv-cs-ai

Decompose, Compare, and Decide: Multimodal LLMs are Implicit Few-Shot Learners

arXiv:2607.00125v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable abilities when analyzing images, yet translating these capabilities to few-shot im

researcharxiv-cs-cv

DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning

arXiv:2607.00341v1 Announce Type: cross Abstract: Large language models achieve strong performance on many reasoning tasks when allowed to externalize intermediate steps as Chain-of-Thought (CoT). How

Does Your ViT Still Need U-Net for Segmentation?

arXiv:2607.00223v1 Announce Type: new Abstract: Medical image segmentation is dominated by U-Net-style encoder-decoder architectures. Vision Transformers (ViTs) overcome the limited receptive field of

DriveVA: Video Action Models are Zero-Shot Drivers

arXiv:2604.04198v2 Announce Type: replace Abstract: Generalization is a central challenge in autonomous driving, as real-world deployment requires robust performance under unseen scenarios, sensor dom

Dual-Informed Vertical Expansion for Multi-Objective Node Selection in Anytime Conflict-Based Search

arXiv:2607.00156v1 Announce Type: new Abstract: Conflict-Based Search (CBS) is a leading exact algorithm for Multi-Agent Path Finding (MAPF), but its high-level node-selection rule is usually treated

safetyarxiv-cs-ro

Efficient Multilingual Reasoning Transfer via Progressive Code-Switching

arXiv:2607.00485v1 Announce Type: new Abstract: Large reasoning models (LRMs) have achieved strong reasoning capabilities in English, yet their performance degrades significantly when required to reas

researcharxiv-cs-cl

Local Ai

EFlow: Learning Evidence Flow for Long-Video Reasoning with Adaptive Reflection

arXiv:2607.00867v1 Announce Type: new Abstract: Long-video reasoning is fundamentally constrained by how models acquire and utilize visual evidence. Existing tool-augmented video frameworks often inte

local-aiarxiv-cs-cv

ELMP: Efficient Learning for Motion Planning via Analytical Policy Gradients

arXiv:2607.00215v1 Announce Type: new Abstract: Neural Motion Planners (NMPs) enable fast reactive motion generation, but adapting them to new environments typically requires recollecting large expert

safetyarxiv-cs-ro

Entropy-Regularized Probabilistic Gates for Sparse Model Discovery in Scarce-Data Federated Learning

arXiv:2607.00275v1 Announce Type: cross Abstract: Federated Learning (FL) is a distributed machine learning (ML) paradigm with collaboration among multiple clients without sharing data. FL is challeng

Evaluating Implicit Biases in LLM Reasoning through Logic Grid Puzzles

arXiv:2511.06160v2 Announce Type: replace Abstract: While recent safety guardrails effectively suppress overtly biased outputs, subtler forms of social bias emerge during complex logical reasoning tas

safetyarxiv-cs-ai

EVOTS: Evolutionary Transformer Search for Time Series Forecasting

arXiv:2607.00154v1 Announce Type: cross Abstract: Evolutionary neural architecture design for multivariate time-series forecasting remains underexplored, with most approaches relying on fixed Transfor

ext{Log}_ext{b}Quant: Quantizing Language Models in Logarithmic Space

model-releasesarxiv-cs-cl

arXiv:2607.01127v1 Announce Type: new Abstract: Quantization has become an invaluable tool to reduce memory requirements and inference speed of modern language models, in particular to make them avail

FCL-COD: Weakly Supervised Camouflaged Object Detection with Frequency-aware and Contrastive Learning

arXiv:2603.22969v2 Announce Type: replace Abstract: Existing camouflage object detection (COD) methods typically rely on fully-supervised learning guided by mask annotations. However, obtaining mask a

researcharxiv-cs-cv

FedIA: Importance-Aware Aggregation for Domain-Robust Federated Graph Learning

arXiv:2509.18171v4 Announce Type: replace Abstract: Federated graph learning (FGL) is a natural paradigm for social-media user graphs, where language communities, regional markets, and service boundar

FlowPath: Learning Data-Driven Manifolds with Invertible Flows for Robust Irregularly-sampled Time Series Classification

arXiv:2511.10841v3 Announce Type: replace-cross Abstract: Modeling continuous-time dynamics from sparse and irregularly-sampled time series remains a fundamental challenge. Neural controlled different

ForAug: Mitigating Biases in Image Classification via Controlled Image Compositions

arXiv:2503.09399v4 Announce Type: replace-cross Abstract: Large-scale image classification datasets exhibit strong compositional biases: objects tend to be centered, appear at characteristic scales, a

safetyarxiv-cs-ai

FRAME: Learning the Adaptation Domain with a Mixture of Fractional-Fourier Experts

arXiv:2607.00162v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) reparameterizes weight updates in a fixed basis: low-rank adapters operate in the spatial domain, while a recent

From Holistic Evaluation to Structured Criteria: Rubrics Across the Evolving LLM Landscape

arXiv:2606.08625v2 Announce Type: replace Abstract: As Large Language Models (LLMs) advance toward open-ended autonomous agents, the mechanisms used to evaluate and guide their behavior must evolve ac

safetyarxiv-cs-cl

From Prediction Uncertainty to Conformalized Distance Fields for Safe Motion Planning

arXiv:2607.00776v1 Announce Type: new Abstract: Safe motion planning in dynamic environments requires reasoning about the uncertainty in predicted obstacle motion without sacrificing real-time perform

safetyarxiv-cs-ro

From Structural Equation Modelling to Double Machine Learning: Robustness Analysis for Survey-Based Research

arXiv:2607.00512v1 Announce Type: new Abstract: Structural equation modelling (SEM) is widely used in survey-based business and information systems research to assess latent constructs and theory-driv

From Technical Metrics to User Perception: A User Study of a Multimodal Human-Robot Interaction System for Object Detection and Grasping

arXiv:2607.00530v1 Announce Type: cross Abstract: Improvements in the technical performance of human--robot interaction (HRI) systems do not automatically translate into differences that human users c

FUMO: Prior-Modulated Diffusion for Single Image Reflection Removal

arXiv:2603.19036v2 Announce Type: replace Abstract: Single image reflection removal (SIRR) is challenging in real scenes, where reflection strength varies spatially and reflection patterns are tightly

Local Ai

GenAU: Language-Grounded Industrial Anomaly Understanding with Vision-Language Models

arXiv:2607.01049v1 Announce Type: new Abstract: Industrial inspection requires more than binary anomaly detection: a practical system should determine whether an anomaly exists, localize the defective

local-aiarxiv-cs-cv

Applications

Geo-ID: Test-Time Geometric Consensus for Cross-View Consistent Intrinsics

arXiv:2603.13859v2 Announce Type: replace Abstract: Intrinsic image decomposition aims to estimate physically based rendering (PBR) parameters such as albedo, roughness, and metallicity from images. W

applicationsarxiv-cs-cv

Geometry-Aware Cross-Height Channel Knowledge Map Prediction for UAV-Assisted Communications With Uncertainty-Guided 3D Sensing

arXiv:2607.00887v1 Announce Type: new Abstract: Low-altitude Unmanned Aerial Vehicles (UAVs) often need to infer channel knowledge across a range of heights from only sparse observations collected at

GimbalDiffusion: Gravity-Aware Camera Control for Video Generation

arXiv:2512.09112v3 Announce Type: replace Abstract: Recent progress in text-to-video generation has achieved remarkable realism, yet fine-grained control over camera motion and orientation remains elu

researcharxiv-cs-cv

GMO-E^2DIT: Grounded Multi-Operation Editing for E-Commerce Images

arXiv:2607.00920v1 Announce Type: new Abstract: Real-world e-commerce image editing often requires multiple, localized, and auditable operations rather than global restyling. This compositional nature

Group-invariant Coresets for Data-efficient Active Learning

arXiv:2607.01089v1 Announce Type: cross Abstract: Active learning reduces labeling cost by querying the most informative unlabeled samples, but standard coreset methods ignore known data symmetries an

researcharxiv-cs-lg

GryphOne: Symbol-Aware Masked Diffusion for Structural Refinement in Offline Handwritten Mathematical Expression Recognition

arXiv:2602.03370v2 Announce Type: replace Abstract: Handwritten mathematical expression recognition (HMER) requires reasoning over diverse symbols and structures, yet autoregressive models struggle wi

Histopathology Multi-modal Embedding for Pathology Composed Retrieval

arXiv:2502.07221v4 Announce Type: replace Abstract: To overcome the black-box nature of predictive AI and the hallucination risks of generative models, retrieval-based models offer an interpretable, e

HyFL-CLIP: Hyperbolic Fine-Tuning of CLIP for Robust Long-Context Understanding

arXiv:2607.00428v1 Announce Type: new Abstract: CLIP (Contrastive Language-Image Pre-training) has become a de facto paradigm for image-text alignment, but it struggles with long-context descriptions

safetyarxiv-cs-cv

Imprint: Online Memory Compression for Long-Horizon Egocentric QA

arXiv:2607.00696v1 Announce Type: new Abstract: Long-horizon egocentric question answering involves answering about events that have occurred hours or days in the past. This requires memory representa

KGS-GCN: Kinematics-Driven Gaussian Splatting and Probabilistic Topology for Skeleton-Based Action Recognition

arXiv:2603.16943v2 Announce Type: replace-cross Abstract: Skeleton-based action recognition is widely applied in sensor-based systems, including human-computer interaction and intelligent surveillance

Know When to Stop: Segment-Level Credit Assignment for Reducing Overthinking

arXiv:2607.00482v1 Announce Type: new Abstract: Reasoning language models frequently overthink: generating extended chains of behaviors such as hedging, approach abandonment, and self contradiction th

researcharxiv-cs-cl

L-Proto: Language-Aware Episodic Prototypical Training for Multilingual Speaker Verification

arXiv:2606.17416v2 Announce Type: replace-cross Abstract: Multilingual speaker verification remains challenging because language-dependent acoustic variability causes speaker identity to become entang

Learning dynamical systems from noisy data with Weak-form Kernel Ridge Regression

arXiv:2607.00257v1 Announce Type: new Abstract: Accurate prediction of complex dynamical systems from noisy measurements remains a significant challenge in scientific computing. Kernel ridge regressio

Learning to Compose: Revisiting Proxy Task Design for Zero-Shot Composed Image Retrieval

arXiv:2607.00374v1 Announce Type: cross Abstract: Composed Image Retrieval (CIR) retrieves a target image from a reference image and a textual modification. While supervised CIR relies on costly tripl

researcharxiv-cs-ai

Leveraging Phase Information to Boost Unrolled Network Learning for Image Deblurring

arXiv:2607.00251v1 Announce Type: cross Abstract: While most image deblurring techniques directly restore the spatial image variable, we propose an amplitude and phase decomposition recognizing the im

LIST3R: Long-sequence Instance-aware 3D Reconstruction

arXiv:2607.00375v1 Announce Type: new Abstract: We present LIST3R, an instance-aware framework for long-sequence 3D reconstruction inspired by the way humans organize spatial memory around stable and

safetyarxiv-cs-cv

LLM-Guided ODE Discovery and Parameter Inference from Small-Cohort Aggregate Data

arXiv:2607.00733v1 Announce Type: cross Abstract: Mechanistic modeling via ordinary differential equations (ODEs) provides interpretable descriptions of complex dynamics and enables inference of under

Logit-Contribution Scoring Identifies Non-Literal Retrieval Heads

arXiv:2607.01002v1 Announce Type: cross Abstract: In long-context use, large language models frequently synthesize answers from the meaning of a relevant context span rather than literally copy-pastin

LuxIT: A Luxembourgish Instruction Tuning Dataset from Monolingual Seed Data

model-releasesarxiv-cs-cl

arXiv:2510.24434v3 Announce Type: replace Abstract: The effectiveness of instruction-tuned Large Language Models (LLMs) is often limited in low-resource linguistic settings due to a lack of high-quali

Mapping the Evaluation Frontier: An Empirical Survey of the Bias-Reliability Tradeoff Across Eleven Evaluator-Agent Conditions

arXiv:2607.00304v1 Announce Type: cross Abstract: The bias-reliability tradeoff conjectures that LLM evaluation systems are constrained in (gamma, H, CV) space, where evaluator coupling (gamma), strat

MedCAGD: Context-Aware Gated Decoder for Efficient Medical Image Segmentation

arXiv:2607.00409v1 Announce Type: new Abstract: Medical image segmentation relies on the ability of encoder-decoder architectures to translate rich feature representations into accurate pixel-level pr

safetyarxiv-cs-cv

MEPA: Multi-Scale Representation Alignment for Visual Autoregressive Modeling with Mixture of Experts

arXiv:2607.00371v1 Announce Type: cross Abstract: Visual AutoRegressive modeling (VAR) has pioneered a coarse-to-fine multi-scale autoregressive generative paradigm, demonstrating strong capabilities