Search: “evaluation”

Stable-Plastic Subspace Construction for Differentially Private Continual LoRA

arXiv:2610.17904v1 Announce Type: new Abstract: Continual learning (CL) adapts pretrained models to a sequence of tasks while retaining knowledge acquired from earlier tasks. When task data are sensit

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Safety

Stein Variational Distributional Reinforcement Learning: Score-Guided Particles for Multivariate Return Distributions

DGX agent

arXiv:2610.17925v1 Announce Type: new Abstract: Decisions that weigh several reward signals against each other require the joint distribution of the return vector. Categorical critics scale exponentia

safetyarxiv-cs-lg

14 Oct 2026

Streamline pathology foundation model by cross-magnification distillation

arXiv:2509.23097v4 Announce Type: replace Abstract: Foundation models (FM) have transformed computational pathology but remain computationally prohibitive for clinical deployment due to their massive

STREGO: A Scalable Implementation of a Trust-Region Framework for Noisy Bayesian Optimization

arXiv:2610.14338v1 Announce Type: cross Abstract: TREGO, a trust-region Bayesian optimization (BO) method for expensive blackbox problems, has convergence guarantees, but only for exact function value

applicationsarxiv-cs-lg

StructZO: Structured Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning

arXiv:2610.16451v1 Announce Type: new Abstract: Fine-tuning large language models at scale is increasingly limited by the memory cost of backpropagation. Zeroth-Order (ZO) optimizers reduce this burde

SuperAI: Merging Capabilities Across Heterogeneous Foundation Models

arXiv:2610.15322v1 Announce Type: cross Abstract: Enabling the reuse and composition of knowledge and capabilities distributed across foundation models is an important step toward building scalable ar

safetyarxiv-cs-lg

SurgiCLAW: An Interpretable Atomic-Skill Agent for Precision Robotic Micromanipulation

arXiv:2610.15766v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) and vision--language--action models have provided robots with new capabilities for long-horizon task und

SYNPRED: A Synergistic Approach to Multimodal Learning for Clinical Prediction

arXiv:2610.18110v1 Announce Type: cross Abstract: Multimodal medical data captures complementary aspects of disease. It provides a comprehensive basis for diagnosis and the identification of biologica

TabMosaic: Unified In-Context Diffusion for Tabular Generative Tasks

arXiv:2610.15699v1 Announce Type: new Abstract: Generative modeling for tabular data has advanced to the point where models can synthesize realistic records, recover missing values, and generate sampl

applicationsarxiv-cs-lg

Agents

TacitVLA: Reasoning Vision-Language-Action Models Without Reasoning Latency

arXiv:2610.17540v1 Announce Type: cross Abstract: Textual reasoning before acting has improved vision-language-action (VLA) models, but at the cost of latency: every action conditioned on the reasonin

agentsarxiv-cs-ro

Targeting the Right Situations: Mutation Testing of Fuzzy-Powered Situation Hyperspace

arXiv:2610.15122v1 Announce Type: new Abstract: Ensuring the safety of autonomous Unmanned Aerial Vehicles (UAVs) operating in underground mines is challenging due to the vast and uncertain Operationa

Temporal Diffusion Bridge Model for Vessel Extraction Using Physics-informed Synthetic Data

arXiv:2610.14105v1 Announce Type: cross Abstract: Accurate artery extraction from X-ray coronary angiography (XCA) is essential for coronary artery disease diagnosis and intervention. However, low ves

Tessera-27B-B-CJK, Zellige AIs new finetune of Qwen with novel approaches to how we think about token savings

model-releasesr-localllama

Tessera-27B-B-CJK is a Qwen3.8-27B coding agent that thinks in compressed CJK, and it spends fewer tokens doing it. Open weights, Apache-2.0. This is our first full 'Tessera' lineup model drop! - Hugg

Testing Central Structure for Complex Networks

arXiv:2610.15659v1 Announce Type: new Abstract: Centrality measures rank nodes even when the observed differences can be explained by ordinary structural variation. We therefore study a preceding ques

Text-Vision Co-Instructed Image Editing

arXiv:2606.16767v2 Announce Type: replace Abstract: Existing image editing methods can be generally categorized into textual instruction-based and visual prompt-based ones. Textual instructions are se

The AI race: China's open-weight models trail US closed models by just 7 months

model-releasesr-localllama

Source: whatmodel.sh, an open source AI leaderboard I built (and launched here yesterday). Every point comes from published benchmark results: 22,113 of them across 987 benchmarks, from 1,011 sources,

The Effect of Layer Ordering in Hybrid Architectures

arXiv:2610.18104v1 Announce Type: new Abstract: Hybrid attention is rapidly becoming the dominant architectural choice for frontier models. Despite their successes, such architectures complicate model

The Human--VLA Communication Gap: What Humans Leave Implicit and What Policies Cannot Recover

arXiv:2610.17746v1 Announce Type: new Abstract: A robot may know how to perform a task yet fail when a human asks for it naturally. We study this human--VLA communication gap by separating an informat

The Language of Looking: Motion Tokens Reveal Domain-Dependent Local Structure in Gaze Sequences

arXiv:2610.16565v1 Announce Type: new Abstract: Human gaze is the primary high-bandwidth interface through which we parse the semantics of our environment. While often modeled as a sequence, the degre

The Optimal Decoder is Tilted Temperature

arXiv:2610.15058v1 Announce Type: new Abstract: Larger sample budgets benefit from higher sampling temperatures in LLMs, but what temperature tuning optimizes and why it works remain poorly understood

Hardware

The Price of Precision: A Calibrated Cost Model for Mixed-Precision LLM Serving

arXiv:2610.15629v1 Announce Type: new Abstract: Choosing a mixed-precision configuration for large language model (LLM) serving trades speed against accuracy. Allocators that use average bit-width or

hardwarearxiv-cs-lg

Thinker-WM: A Unified World Model with Shared Multimodal Representations for Embodied Intelligence

arXiv:2610.18447v1 Announce Type: cross Abstract: World models have emerged as a promising paradigm for embodied AI, yet existing systems often remain fragmented in the modalities they model and the f

Through the PRISM: Preference Representation in Intermediate States of Video Diffusion Models

arXiv:2606.20310v2 Announce Type: replace Abstract: Video reward models are central to aligning video diffusion models with human preferences, yet existing ones are external vision-language models tha

TIDE: Trajectory-Informed Skill Distillation for Efficient Text-to-Video Prompt Optimization

arXiv:2610.15098v1 Announce Type: new Abstract: Text-to-video (T2V) models are highly sensitive to prompt specificity, while iterative prompt optimization typically improves generation quality only th

Time Window Optimization for Motor Imagery Classification via Temporal Structure Embedded Reinforcement Learning

arXiv:2610.16921v1 Announce Type: cross Abstract: Online motor imagery-based brain-computer interfaces (MI-BCIs) typically decode continuous EEG using fixed-length sliding windows that may be misalign

TLA-Verus: Generating and Solving Temporal Proof Obligations with LLM Agents

arXiv:2610.14923v1 Announce Type: new Abstract: The TLA+ (temporal logic of actions) formal specification toolkit has seen widespread adoption in modeling modern distributed software systems including

safetyarxiv-cs-lg

Token-Budgeted Candidate Retrieval for 3D Scene-Grounded VLMs: Category Names vs. Pairwise Geometry

arXiv:2610.14207v1 Announce Type: new Abstract: Under a fixed context budget, which objects and relations should a 3D scene-grounded VLM see first? On ScanNet indoor referring benchmarks (Dai et al.,

TokenPB: Enabling VLA Action Self-Verification via VLM Token Probability Bucketing

arXiv:2603.18091v2 Announce Type: replace Abstract: Test-time sampling can improve Vision-Language-Action (VLA) policies, but only if the model can efficiently select a good action from multiple candi

applicationsarxiv-cs-cv

Agents

TopoCurate:Modeling Interaction Topology for Tool-Use Agent Training

arXiv:2603.01714v2 Announce Type: replace Abstract: Training tool-use agents typically relies on outcome-based filtering: Supervised Fine-Tuning (SFT) on successful trajectories and Reinforcement Lear

agentsarxiv-cs-lg

TopoPilot: Reliable Conversational Workflow Automation for Topological Data Analysis and Visualization

arXiv:2603.25063v2 Announce Type: replace-cross Abstract: Recent agentic systems demonstrate that large language models can generate complex codebases from natural language prompts. Despite this progr

Toward Guarantees for Clinical Reasoning in Vision Language Models via Formal Verification

arXiv:2602.24111v2 Announce Type: replace Abstract: Vision-language models (VLMs) show promise in drafting radiology reports, yet they frequently suffer from logical inconsistencies, generating diagno

Toward Zero-Shot Point Cloud Registration Across Diverse Scales, Scenes, and Sensor Setups

arXiv:2601.02759v2 Announce Type: replace Abstract: Some deep learning-based point cloud registration methods struggle with zero-shot generalization, often requiring target-domain retraining, fine-tun

Towards Optimality in Active Preference Learning

arXiv:2602.01581v2 Announce Type: replace Abstract: Aligning large language models (LLMs) depends on high-quality datasets of human preference labels, which are costly to collect. Although active lear

applicationsarxiv-cs-lg

Towards Privacy-Preserving Thermal Human Perception from Dataset to Deployment

arXiv:2610.14846v1 Announce Type: new Abstract: Indoor human perception is the foundation for smart homes and healthcare. However, RGB cameras raise privacy concerns in private indoor environments, wh

applicationsarxiv-cs-cv

TRACE: Efficient Transfer Learning for Neural Whole-Body Control Across Humanoid Embodiments

arXiv:2610.17999v1 Announce Type: new Abstract: Humanoid behavior foundation models (BFMs) enable diverse whole-body control, but adapting a pretrained controller to a new embodiment remains challengi

Tracing where LLM 'slop' style comes from in the model and in training, and cutting it out [R]

model-releasesr-machinelearning

I wanted to find where the recognizable assistant style (em dashes, 'it's not X, it's Y', lists of three, buzzwords) lives in a model and which training stage installs it. Where it lives: in Qwen3-4B-

TurnCost: Turns, Not Observations: Cache-Aware Loop Engineering for Coding Agents

arXiv:2610.15093v1 Announce Type: cross Abstract: AI coding agents operate in iterative loops: they modify code, run tools, inspect the results, and decide what to do next. We call the design of this

Uncertainty-Aware Semi-Supervised Framework with Supervised Contrastive Learning for Sugarcane Leaf Disease Detection

arXiv:2610.17996v1 Announce Type: new Abstract: Sugarcane leaf diseases severely impact crop yield and quality, making accurate and timely detection critical for sustainable agriculture. Conventional

Uncovering the Generative Landscape of Diffusion Models: A Spectral-Guided Quality-Diversity Diffusion Framework

arXiv:2610.15724v1 Announce Type: new Abstract: Denoising Diffusion Probabilistic Models have emerged as powerful generative priors across domains ranging from molecular design to high-resolution imag

Understanding and Mitigating Training Instability in Large-Scale Recommender Systems: A Cascade Perspective

arXiv:2610.14394v1 Announce Type: cross Abstract: Training large-scale recommender systems on dynamic industrial platforms, such as Short-Form Video (SFV) services with billions of daily interactions,

UniMetric: Universal Metric Scale Recovery for Visual Geometry Foundation Models

arXiv:2610.16945v1 Announce Type: new Abstract: Recent advances in multimodal foundation models, exemplified by GPT-6 Astra, raise the prospect of general-purpose embodied reasoning and planning. Usin

Tutorials

UniW(A)M: A Unified Mixture-of-Experts Framework for World and World-Action Models

arXiv:2610.18697v1 Announce Type: cross Abstract: World models (WMs) and world-action models (WAMs) focus on future world prediction and executable action generation, respectively. Although these mode

tutorialsarxiv-cs-cv

Unrolled Neural Networks for Constrained Optimization

arXiv:2601.17274v2 Announce Type: replace Abstract: We develop unrolled neural networks to solve constrained optimization problems, offering accelerated, learnable counterparts to dual ascent (DA) alg

Unsupervised and Supervised Approaches for Infrared Small Target Detection : Overview, Challenges and Perspectives (Part 2)

arXiv:2610.18291v1 Announce Type: new Abstract: Since the rise of supervised deep learning modelet dets, researchers has attempt to solve infrared small targection using various models like convention

Local Ai

Using Line Segment Tracking to enable ML-based Track Reconstruction in CMS

arXiv:2610.15963v1 Announce Type: cross Abstract: High-pileup conditions in CMS during the HL-LHC era make charged-particle tracking increasingly challenging as detector occupancy and combinatorics gr

local-aiarxiv-cs-lg

Value-Preserving Action Quantization

arXiv:2610.17252v1 Announce Type: cross Abstract: Search-based policy learning, such as Monte Carlo tree search (MCTS), offers the flexibility to trade runtime computation for data efficiency and adap

Variational Filtering for Bayesian Last Layers with an Independent Binary Probit Surrogate

arXiv:2610.16578v1 Announce Type: cross Abstract: Modern deep classifiers trained by gradient descent need many passes over the data to become accurate, and even then are not always well calibrated; p

VbotNav-0: Asynchronous Cloud-Edge Dual-Policy Navigation across Indoor and Outdoor Environments

arXiv:2610.14634v1 Announce Type: new Abstract: Continuous indoor-outdoor navigation connects destination-level reasoning with motion decisions that must respond to current observations. We present Vb