Search: “evaluation”

Hearing Like Humans? Sound Symbolism and Perceptual Alignment in Speech Language Models

arXiv:2607.10162v2 Announce Type: replace-cross Abstract: Sound symbolism, the human tendency to map speech sounds to perceptual qualities such as roundness or sharpness, arises primarily from the aco

safetyarxiv-cs-cl

Human

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Safety

HexaGripper: A Single-Actuator, Winch-Deployed Gripper for Autonomous Aerial Parcel Collection

DGX agent

arXiv:2610.08259v1 Announce Type: new Abstract: Autonomous aerial parcel collection remains constrained by package-transfer operations that require manual loading, landing, or dedicated ground infrast

safetyarxiv-cs-ro

7 Oct 2026

Honesty over Accuracy: Trustworthy Language Models through Reinforced Hesitation

arXiv:2511.11500v3 Announce Type: replace Abstract: Modern language models fail a fundamental requirement of trustworthy intelligence: knowing when not to answer. Despite achieving impressive accuracy

researcharxiv-cs-lg

How Much Evidence Should a Coding Agent's Self-Correction Carry? Adaptive Dirichlet Evidence for Self-Distillation

arXiv:2610.08514v1 Announce Type: new Abstract: Execution feedback lets coding agents revise programs and learn from their own corrections. A correction's learning weight should reflect both the trans

How Well Do LLMs Reason with Noisy Evidence? An Active Visual Reasoning Benchmark

arXiv:2610.07751v1 Announce Type: new Abstract: Real-world reasoning rarely reduces to static question answering: agents must actively gather information from tools and sensors that are often noisy an

Hypergraph-Enhanced Dual Convolutional Network for Bundle Recommendation

arXiv:2312.11018v3 Announce Type: replace-cross Abstract: Bundle recommendation ranks sets of related items rather than isolated items. Its central challenge is to connect user preferences, item inter

IdeaAnchor: Teaching LLMs to Turn Literature into Research Ideas

arXiv:2610.08781v1 Announce Type: cross Abstract: Scientific research often begins by synthesizing ideas from a set of related papers to identify gaps and formulate new directions. However, training l

Identifiable World Models from Pretrained Diffusion Representations

arXiv:2610.07028v1 Announce Type: new Abstract: Diffusion-based world models can generate and predict trajectories in high-dimensional dynamical systems, but predictive accuracy does not imply that th

Identity-Conditioned Score Fusion for Open-Set Person Re-Identification

arXiv:2610.07366v1 Announce Type: new Abstract: Robust person re-identification often combines complementary cues such as face, gait, and body shape. While adaptive fusion typically targets query qual

Image Bitstream Fine-grained Understanding for Privacy-Friendly AIoT

arXiv:2610.08414v1 Announce Type: new Abstract: Image Bitstream Fine-grained Understanding (IBFU) aims to directly perform fine-grained classification and semantic description generation from encoded

Improving Mixup Calibration with Wasserstein Distributionally Robust Optimization

arXiv:2506.17874v3 Announce Type: replace-cross Abstract: In many real-world applications, ensuring the robustness and stability of deep neural networks (DNNs) is crucial, particularly for image class

Incidental information contaminates patient notes and disrupts clinical reasoning in large language models

arXiv:2610.08585v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly relied upon to support ambient documentation and clinical reasoning. Here we examine the impact of a failu

researcharxiv-cs-cl

Independent Multi-Agent Reinforcement Learning with Counterfactual Semantic-Social World Models

model-releasesarxiv-cs-lg

arXiv:2610.07704v1 Announce Type: cross Abstract: Fully decentralized multi-agent reinforcement learning (MARL), also referred to as independent learning, requires each agent to learn and act using on

Inference and learning in sparse autoencoders as natural gradient flow

arXiv:2610.07389v1 Announce Type: cross Abstract: Sparse autoencoders are widely used to uncover interpretable features in neural networks, yet reliable recovery remains difficult when features overla

Local Ai

Inference-Time Projection for Physically Valid Biomolecular Diffusion Models

arXiv:2610.07037v1 Announce Type: new Abstract: AlphaFold 3-style cofolding models predict biomolecular complexes with high structural accuracy, yet a large fraction of their outputs are physically in

local-aiarxiv-cs-ai

Applications

InStyle: Instant Appearance Stylization of 3D Shapes

arXiv:2512.03683v2 Announce Type: replace Abstract: 3D stylization is central to game development, virtual reality, and digital arts, where the demand for diverse assets calls for scalable methods tha

applicationsarxiv-cs-cv

Introducing Google Cloud’s U4 compute: Enabling ultra-low latency trading

model-releasesgoogle-cloud-ai

In capital markets, operational success is built on predictable performance and low latency, where even tiny variations in packet timing alter queue priority and trade execution. At the same time, bot

IronMan: Information-Constrained Video-Action Learning for Robot Manipulation

arXiv:2610.07961v1 Announce Type: new Abstract: Video Action Models (VAMs) couple visual dynamics modeling with action generation for robot manipulation. However, video representations are not natural

safetyarxiv-cs-ro

Agents

Joint Workflow and Prompt Optimization for User Behavior Simulation

arXiv:2610.07663v1 Announce Type: cross Abstract: User behavior simulation is the computational modeling of user interactions within information systems through the use of simulated agents in place of

agentsarxiv-cs-ai

JudgeMoE: Distributional Aggregation for LLM-as-a-Judge

model-releasesarxiv-cs-cl

arXiv:2610.07109v1 Announce Type: new Abstract: When an LLM judge scores an output, its score distribution retains uncertainty and disagreement information that is lost after scalar compression. We in

Knowing When Not to Answer: Cross-Domain and Multi-Turn Generalization of Latent Underspecification Signals

arXiv:2610.08413v1 Announce Type: cross Abstract: Large language models routinely answer questions that cannot be answered from the information given, and in dialogue they answer before enough has bee

LARK: A Low-Cost, Accurate, Occlusion-Resilient, Kalman Filter-Assisted Tracking System for Image-Guided Surgery

arXiv:2610.07561v1 Announce Type: new Abstract: Image-guided surgery (IGS) depends on accurate tracking of surgical instruments to provide real-time navigation relative to anatomical structures. Comme

researcharxiv-cs-cv

Latent space bias directions in LLMs capture confidence, not fairness

arXiv:2610.08559v1 Announce Type: cross Abstract: Activation steering has gained popularity as a lightweight inference-time debiasing technique for large language models. However, prior work reports t

safetyarxiv-cs-ai

Later Is Better: Token Reduction for ViTs Under Distribution Shift

arXiv:2610.07758v1 Announce Type: cross Abstract: Training-free token reduction accelerates vision transformers by removing redundant tokens across layers, recovering most of the original accuracy at

LeanPlan: Optimal Planning with LLM-Generated Heuristics and Admissibility Proofs

arXiv:2610.08246v1 Announce Type: new Abstract: Frontier large language models (LLMs) can generate heuristic functions that guide search to achieve state-of-the-art performance in satisficing planning

Tutorials

Learning from Failures: A Failure-Driven Prompt Refinement for LLM-Based Vulnerability Analysis

arXiv:2610.08405v1 Announce Type: cross Abstract: Large Language Models have emerged as promising tools for software vulnerability analysis, but their effectiveness depends heavily on prompt design. E

tutorialsarxiv-cs-ai

Learning When to Refine: Long-Horizon Reinforcement Learning for Budgeted Neural-Operator PDE Solvers

arXiv:2610.06883v1 Announce Type: cross Abstract: Neural operators provide fast surrogates for time-dependent PDEs, but autoregressive deployment creates a refinement-allocation problem: prediction er

LiDAR Resolution Recovery via Foundation-Model-Guided Diffusion

arXiv:2610.08620v1 Announce Type: new Abstract: High-beam-count LiDAR sensors are costly, yet many perception pipelines require dense angular sampling. Using a pretrained Stable Diffusion model as the

researcharxiv-cs-cv

Linear Bandits under Exact Sliding-Window Constraints

arXiv:2610.08745v1 Announce Type: new Abstract: We study linear bandits under exact sliding-window constraints, where every consecutive block of actions must belong to a prescribed feasible set. In th

Linear Fitness Subspace in Protein Language Models Enables Sample-Efficient Directed Evolution

arXiv:2610.07607v1 Announce Type: cross Abstract: Model-guided directed evolution seeks to identify high-fitness protein variants under limited oracle budgets. Protein language models (PLMs) provide r

Lost in the bf16 Cast: Exporting Ternary Language Models Can Revert Most Low-Learning-Rate Code Changes

model-releasesarxiv-cs-cl

arXiv:2610.07853v1 Announce Type: cross Abstract: Ternary language models such as BitNet b1.58, Falcon-E and BitCPM are fine-tuned with higher-precision latent weights and deployed as ternary codes pr

Applications

Low-Rank and Structured Sparse Tensor Decomposition for Anomaly Detection in Multivariate Functional Data

arXiv:2610.06930v1 Announce Type: cross Abstract: Multivariate functional data arise in many modern manufacturing systems, where multiple sensors record densely sampled process trajectories. Monitorin

applicationsarxiv-cs-lg

Matching Object or Relation? Tracing Abstract Reasoning Inside VLMs

arXiv:2610.07646v1 Announce Type: new Abstract: Vision Language Models (VLMs) excel on visual benchmarks but fail systematically on tasks requiring abstract reasoning. Existing benchmarks document thi

Medical Image Alignment Assessment as a Test of Generalist Visual Reasoning in Frontier Multimodal Models

arXiv:2610.06896v1 Announce Type: new Abstract: Frontier multimodal large language models (MLLMs) are increasingly positioned as general purpose visual reasoners as part of the quest for artificial ge

MemFLoRA: Memory-Floor LoRA for CNN Adaptation at the Edge

arXiv:2610.08669v1 Announce Type: cross Abstract: On-device learning is necessary when the model encounters user-,sensor-, or environment-specific shifts after deployment. Although parameter-efficient

Local Ai

Memory-Efficient Expert Routing for Distributed MoE Training

arXiv:2610.07333v1 Announce Type: cross Abstract: As Mixture-of-Experts (MoE) models scale toward hundreds of experts and higher top-k routing, memory efficiency in distributed training becomes a crit

local-aiarxiv-cs-ai

Mission-Aware Attestation Envelopes for Time-Critical Autonomous Action: A Hardware-in-the-Loop V2I Study

model-releasesarxiv-cs-ro

arXiv:2610.08771v1 Announce Type: cross Abstract: An autonomous system that asks for a privileged physical action is usually gated on integrity evidence: a platform proves what it is running, and the

Agents

Mitigating Concept Drift in QoS Prediction for Teleoperation of Autonomous Vehicles Using Historic Data

arXiv:2610.08297v1 Announce Type: cross Abstract: Teleoperation serves as the fallback solution to autonomous driving but reliable functions of the teleoperation require a certain amount of mobile net

agentsarxiv-cs-ai

Modeling Time-Dependent Responses of Optical Compressors with Selective State Space Models

arXiv:2408.12549v4 Announce Type: replace-cross Abstract: This paper presents a method for modeling optical dynamic range compressors using deep neural networks with Selective State Space models. The

MoonGS: High-quality Representation of the Lunar Surface via Gaussian Splatting Using Robust Depth Features from Image Pairs

arXiv:2610.07110v1 Announce Type: new Abstract: High-quality 3D reconstruction of lunar terrain from sparse rover images is indispensable for autonomous lunar exploration, but remains challenging beca

MS-ECG-FM: Towards a More Universal Electrocardiogram Foundation Model for Health Monitoring using Multi-source Contrastive Learning

arXiv:2610.07662v1 Announce Type: new Abstract: Electrocardiography (ECG) records the electrical activity of the heart, aiding diagnosis by detecting abnormalities in cardiac function. ECG foundation

Multimodal Knowledge Distillation for Gastric Adenocarcinoma Classification from Whole-Slide Images

arXiv:2610.07913v1 Announce Type: cross Abstract: Gastric adenocarcinoma (GA) is a leading cause of cancer-related mortality worldwide, and accurate histopathological subtype classification from whole

Agents

nanoMuse: An Open-Source Personal Agent for Every Device You Own

arXiv:2610.08699v1 Announce Type: new Abstract: Assistants from 2011 answered and waited, and agents from 2023 did a task and stopped. In September 2026 Meta's Muse showed an agent for one person, wit

agentsarxiv-cs-ai

Navigation with RF Cues: Embodied Perception Action under Multipath Uncertainty

model-releasesarxiv-cs-ro

arXiv:2610.08105v1 Announce Type: new Abstract: Smart factory inspection requires robots to reach connected equipment without a prior map or known target coordinates. Radio frequency (RF) signals from

Neural Algorithmic Reasoning for Graph Saddle Point Problems

arXiv:2610.07255v1 Announce Type: new Abstract: Neural algorithmic reasoning, or aligning a neural network with an algorithmic paradigm, has emerged as an approach to solving polynomial-time-solvable

Local Ai

Neural Global Optimization via Iterative Refinement from Noisy Samples

arXiv:2604.03614v3 Announce Type: replace-cross Abstract: Global optimization of black-box functions from noisy samples is a fundamental challenge in machine learning and scientific computing. Traditi

local-aiarxiv-cs-ai

Neuromotor Hierarchy Network: Physiological Inductive Biases for Robust Generalization in sEMG Decoding

model-releasesarxiv-cs-lg

arXiv:2610.07713v1 Announce Type: new Abstract: Surface electromyography (sEMG) provides a wearable, noninvasive interface to neuromuscular activity for movement decoding and human-computer interactio

Neutrosophic Ensemble Classification for Uncertainty-Aware Bearing Fault Detection: Evidence from Laboratory and Variable-Speed Industrial Benchmarks

arXiv:2610.06880v1 Announce Type: cross Abstract: Machine learning classifiers for bearing fault detection produce scalar confidence scores that conflate confident errors with genuinely ambiguous pred