Search: “evaluation”

arXiv:2610.03516v1 Announce Type: cross Abstract: World action models (WAMs) have advanced robot control by predicting how observations and actions evolve over time. Despite this progress, RGB and act

Research: Qwen3.8 27B addition in words Colin Frasier posted on Bluesky about an experiment he ran over two years ago using GPT-4o to see how well it could 'compute the sum but return the answer in wo

Auto-generated synthesis of 10865 entries about arxiv-cs-cl

On October 3, 2026 Yohei Nakajima posted a brief tweet praising the use of multiple AI coding assistants—Codex, Claude, Gemini, and Grok Bot—with a musical note emoji. The message also contains a Java

arXiv:2610.00969v1 Announce Type: cross Abstract: Large language models (LLMs) have been increasingly used for financial document analysis, including earnings call transcripts (ECTs). Beyond generatin

arXiv:2610.00125v1 Announce Type: cross Abstract: One-Pixel Attacks (OPAs) represent one of the most extreme demonstrations of adversarial fragility in deep learning, where modifying a single pixel ca

arXiv:2610.01894v1 Announce Type: new Abstract: Machine learning (ML) has emerged as a promising approach for improving diffusion MRI (dMRI) tractography, a task that remains limited by the intrinsic

arXiv:2610.00952v1 Announce Type: cross Abstract: Recaptioned image-text corpora are now standard for text-to-image (T2I) training, with vision--language model (VLM) captioners replacing sparse alt-te

arXiv:2610.00126v1 Announce Type: cross Abstract: Agent developers increasingly compare prompts, tools, policies, and diagnosis algorithms through simulator-grounded verifiers. A verifier can neverthe

arXiv:2610.00825v1 Announce Type: new Abstract: Dubbing quality control requires a reference-free judge that can determine whether a candidate text line matches a speaker's visible articulation in bot

arXiv:2610.00831v1 Announce Type: new Abstract: A typed decision is a choice among a fixed set of options, returned as a probability rather than as text. Systems that need typed decisions today use mo

arXiv:2610.00854v1 Announce Type: new Abstract: Frontier vision-language models (VLMs) combine scene estimation, interaction grounding, and executable actions. Understanding how these abilities suppor

arXiv:2610.02098v1 Announce Type: new Abstract: Mechanistic interpretability aims to recover the internal computations responsible for model behavior. Progress in automated circuit discovery is often

arXiv:2610.00988v1 Announce Type: new Abstract: Cryptic ligand-binding pockets are not apparent in experimentally determined apo structures, making them difficult to identify from unbound receptor geo

arXiv:2610.01519v1 Announce Type: cross Abstract: Neuro-Symbolic (NeSy) predictors incorporate prior knowledge into the prediction process of neural networks, ensuring that outputs satisfy specified c

arXiv:2610.01595v1 Announce Type: cross Abstract: Video Large Language Models (VideoLLMs) receive frames in sequential order and interpret how visual content evolves along the temporal axis, yet tempo

arXiv:2610.00092v1 Announce Type: cross Abstract: Data agents over structured sources must fit database schema into the model's context window. Large catalogs can span many databases and thousands of

arXiv:2510.24046v2 Announce Type: replace-cross Abstract: Existing tabular data generation methods primarily focus on matching statistical distributions between real and synthetic data, often overlook

arXiv:2610.00431v1 Announce Type: cross Abstract: Continual parameter-efficient fine-tuning for large language models (LLMs) must balance retention of previously acquired knowledge, adaptation to new

arXiv:2610.00673v1 Announce Type: cross Abstract: Looped language models increase effective depth by repeatedly applying a shared block of layers, but existing large-scale recipes require multi-stage

arXiv:2610.00197v1 Announce Type: new Abstract: We investigate automated rewards for training language models in conversational humor, focusing on reward exploits and countermeasures. Two approaches a

arXiv:2610.01253v1 Announce Type: new Abstract: Quantum Reinforcement Learning (QRL) integrates reinforcement learning with parameterized quantum circuits and is a promising approach to combinatorial

arXiv:2610.00328v1 Announce Type: new Abstract: Structured tool calls often fail after only a small number of fields violate a schema or an execution contract. Regenerating the complete object enlarge

arXiv:2610.01124v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models are often pretrained with a fixed channel vocabulary or a limited set of montages, making transfer diffic

arXiv:2610.00582v1 Announce Type: new Abstract: Aesthetic image cropping aims to identify the optimal crop of an image in terms of aesthetics and composition. While supervision based on annotated data

arXiv:2610.00415v1 Announce Type: new Abstract: Machine-learning surrogates accelerate physical simulation, but lower prediction error need not coincide with lower error in physically relevant flow st

arXiv:2610.01045v1 Announce Type: new Abstract: A chatbot that says 'I will remind you tomorrow' will not run again until the user writes. We call such a promise an empty commitment: a promise of an a

arXiv:2608.01772v2 Announce Type: replace Abstract: LLM agents increasingly run policy-bound enterprise workflows, where they must apply rules consistently and stay auditable. Deploying such an agent

arXiv:2610.00492v1 Announce Type: cross Abstract: When Isaac Newton discovered the law of gravitation, he did so through an iterative process of analyzing observed data such as planetary patterns, fin

arXiv:2610.00136v1 Announce Type: cross Abstract: This paper presents a reproducible, educational study of evasion attacks in image classification and text classification. A compact convolutional netw

arXiv:2610.02010v1 Announce Type: cross Abstract: Invisible watermarking has become a central tool for tracing AI-generated images, but its robustness against adaptive removal attacks remains an open

arXiv:2610.01105v1 Announce Type: new Abstract: Autonomous robots on one-shot missions run over horizons far longer than the trajectories seen during training, under a fixed onboard compute budget. We

arXiv:2610.00049v1 Announce Type: new Abstract: Graphics processing unit (GPU) generations scale matrix, special-function, and memory pipelines at different rates, so kernel bottlenecks move as hardwa

arXiv:2610.01967v1 Announce Type: new Abstract: As large language models (LLMs) keep growing in size and complexity, their training frameworks evolve at a rapid pace as well. Therefore, continuous int

arXiv:2610.00885v1 Announce Type: cross Abstract: Coding agents increasingly automate Lean proof development, but successful compilation alone does not establish that a candidate proves the intended s

arXiv:2610.00573v1 Announce Type: new Abstract: Query-aware keyframe selection enables multimodal large language models (MLLMs) to process long videos using only a small set of question-relevant frame

arXiv:2610.01864v1 Announce Type: cross Abstract: How can we understand what a music foundation model has learned extit{internally}? Most interpretability approaches, such as probing and Sparse Autoen

arXiv:2610.01019v1 Announce Type: new Abstract: Robotic world models predict action-conditioned future scenes, providing a foundation for understanding action outcomes. However, turning alternative pr

arXiv:2610.02110v1 Announce Type: new Abstract: Transparent and specular surfaces pose a serious challenge to LiDAR-based SLAM and navigation because laser returns may pass through glass, leaving coll

arXiv:2610.01985v1 Announce Type: new Abstract: Environmental robotic sampling requires considering the dual influence of water currents on robotic motion and particle transport. Existing marine robot

arXiv:2610.02186v1 Announce Type: cross Abstract: Molecular learning models are strongly shaped by their underlying representations. Yet standard sequential and graph formalisms struggle to explicitly

arXiv:2610.02197v1 Announce Type: new Abstract: Video generation models have achieved remarkable visual fidelity and have strong potential to become general-purpose world simulators. Despite this prog

arXiv:2610.01605v1 Announce Type: cross Abstract: Reliable visual reasoning requires composing multiple visual observations and returning consistent answers to logically equivalent questions. We intro

arXiv:2610.02089v1 Announce Type: cross Abstract: As robotic hardware and learning methods advance, humanoids need tools to perform tasks beyond their inherent physical limits. Successful tool use req

arXiv:2610.00648v1 Announce Type: new Abstract: AI coding agents are ubiquitous in engineering workflows amongst industry and academia. Yet, despite their use in app coding, relatively less attention

MCP, CLI, and skills are three ways to extend an agent with the same platform. The question is no longer which one wins. It is where the agent runs, and who is asking. The post Introducing Arize AX MC