Search: “evaluation”

arXiv:2607.03158v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to implement algorithms from research manuscripts, but papers often leave implementation choices im

arXiv:2607.04640v1 Announce Type: new Abstract: We study how correctness is assembled inside aligned language models, not only whether the final answer is right. Using layer-wise difference-in-differe

Ethan Mollick discusses how token costs for AI systems shouldn't be viewed purely as expenses, arguing that some token usage represents research and development spending to understand AI capabilities,

'Ghost memory' is a real problem with agents. You might have seen the issue where a long-running agent still confidently repeats a user fact that stopped being true weeks ago? New research names the f

The automotive industry is at a pivotal crossroads as it hits the gas on adopting new technology. The era of the traditional connected vehicle has shifted into the age of the software-defined vehicle

introducing tinyrouter i reverse engineered the routing architecture behind Skana AI's Fugu and built replication for open frontier models. it's a tiny ~10K parameter LLM router that learns which mode

arXiv:2512.13836v2 Announce Type: replace-cross Abstract: Autonomous driving requires reliable collision avoidance in dynamic environments. Nonlinear Model Predictive Controllers (NMPCs) are suitable

arXiv:2607.01974v1 Announce Type: cross Abstract: This technical report describes our system for Task 1 of the DCASE 2026 Challenge, which aims to classify heterogeneous audio recordings according to

arXiv:2607.01554v1 Announce Type: new Abstract: This study proposes a reconfigurable rocker-bogie mechanism that achieves efficient turning motion with a small number of actuators while maintaining hi

arXiv:2607.02005v1 Announce Type: new Abstract: This paper presents OCD SLAM, a dynamic stereo visual SLAM framework that extends ORB-SLAM2 by jointly addressing dynamic objects and dynamic features i

arXiv:2504.03711v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI)-driven electronic design automation (EDA) techniques have been extensively explored for VLSI circuit design appli

arXiv:2607.02141v1 Announce Type: new Abstract: Most LP-from-text benchmarks are static datasets of word problems written and labeled by hand. Once such a dataset is released, its size is fixed, its d

arXiv:2604.08169v2 Announce Type: replace Abstract: Alignment in LLMs is more brittle than commonly assumed: misalignment can be induced by adversarial prompts, benign fine-tuning, emergent misalignme

arXiv:2607.01287v1 Announce Type: cross Abstract: Accompanying a group of humans is an essential aspect of developing human-like social cognition in robots. However, human groups typically do not foll

arXiv:2607.01256v1 Announce Type: cross Abstract: Overwhelmed courts in the United States review millions of default judgments each year. Unfortunately, such manual reviews are time-consuming and pron

arXiv:2607.01776v1 Announce Type: cross Abstract: In the age of AI, what will be good knowledge? This article, which is accepted and forthcoming in a special issue of Modern Fiction Studies on 'Cultur

arXiv:2510.04520v2 Announce Type: replace Abstract: Accurate auto-formalization of theorem statements is essential for advancing automated discovery and verification of research-level mathematics, yet

arXiv:2607.02137v1 Announce Type: cross Abstract: We study timestep allocation for score-based diffusion sampling, where a learned reverse-time dynamics is discretized on a finite grid. Uniform and ha

arXiv:2607.01257v1 Announce Type: cross Abstract: The rapid digitalisation of financial systems has improved operational efficiency and financial inclusion while simultaneously increasing exposure to

arXiv:2607.01959v1 Announce Type: cross Abstract: We propose a model agnostic methodology to measure lag relevance in machine learning forecasting models applied to univariate time series. Particularl

arXiv:2607.01313v1 Announce Type: cross Abstract: In practice, most commercial LLM providers do not publicly release details of underlying LLM architectures. However, prior work has shown that given l

arXiv:2607.02195v1 Announce Type: new Abstract: General-purpose vision-language-action models benefit from large vision-language priors, but effective manipulation also requires anticipating action-re

arXiv:2603.22435v2 Announce Type: replace-cross Abstract: 'Code-as-Policy' considers how executable code can complement data-intensive Vision-Language-Action (VLA) methods, yet their effectiveness as

arXiv:2607.01295v1 Announce Type: cross Abstract: Acoustic imaging visualization is a core methodology in acoustics, enabling spatial analysis of sound sources and acoustic scenes. However, limited se

arXiv:2607.02134v1 Announce Type: new Abstract: Scientific machine learning papers typically make computational claims, e.g., that the relative mean square error is less than 5% or that the 95% predic

arXiv:2607.02222v1 Announce Type: cross Abstract: Vision-Language Navigation has increasingly emphasized high-level instruction reasoning, memory, global map construction, and instruction decompositio

arXiv:2607.01709v1 Announce Type: new Abstract: Agents are increasingly used to construct workflows and assist humans in completing recurring tasks more efficiently. As these workflows become repeated

arXiv:2506.06323v2 Announce Type: replace-cross Abstract: Model-free and reinforcement learning-based adaptive filtering methods are gaining traction for denoising in dynamic, non-stationary environme

arXiv:2607.01417v1 Announce Type: new Abstract: Conditional inference trees (CIT) and conditional inference forests (CIF) reduce split-selection bias by testing features before choosing split threshol

arXiv:2607.01916v1 Announce Type: new Abstract: Large language model agents can repair real repository issues, but they often spend large context budgets on whole-file reads, broad searches, and long

arXiv:2607.02245v1 Announce Type: new Abstract: Mental health disorders affect nearly one billion people globally, yet 75% of individuals in low- and middle-income countries receive no treatment due t

arXiv:2607.01646v1 Announce Type: new Abstract: State-of-the-art large language model (LLM) training takes tens of thousands of graphics processing units (GPUs) for months and encounters failures acro

arXiv:2607.01849v1 Announce Type: cross Abstract: Musical performance involves executing a set of high-level musical instructions, yet recovering those instructions from the performance is a challengi

arXiv:2607.02390v1 Announce Type: new Abstract: How can Large Language Models (LLMs) solve problems they currently cannot? Repeated sampling scales test-time compute but GPU cost grows linearly with a

arXiv:2607.01557v1 Announce Type: cross Abstract: Large Language Models (LLMs) often struggle with persuasion in high-stakes scenarios. People's individual personalities and concerns require tailored

arXiv:2607.02374v1 Announce Type: new Abstract: Personalization changes what a model says to a user; we show that it can also change the reasoning trajectory used to justify the response. Modern LLMs

arXiv:2607.01276v1 Announce Type: cross Abstract: Embedding models are essential components of modern Information Retrieval (IR) systems, yet they are typically hidden behind APIs. Recent works have s

arXiv:2607.02501v1 Announce Type: new Abstract: Embodied AI models now span vision-language-action (VLA) models and world-action models (WAMs), but practical deployment remains fragmented across model

arXiv:2607.02118v1 Announce Type: new Abstract: Scientific Fitness Coaching (SFC) is typically delivered by human professionals, making it costly and inaccessible to many. While recent advances in Lar

arXiv:2607.01275v1 Announce Type: cross Abstract: Variational Autoencoders (VAEs) commonly assume a standard isotropic Gaussian prior over the latent space, an assumption that often fails to capture t

arXiv:2607.01280v1 Announce Type: new Abstract: Programming-by-example systems infer programs from a small set of input-output examples. Robust PBE work usually models wrong examples as samples from a

arXiv:2607.01824v1 Announce Type: new Abstract: Crowdsourced fact-checking systems have been adopted by major social media companies such as X, Meta, TikTok and Google with the aim of combating mislea

arXiv:2606.13501v2 Announce Type: replace-cross Abstract: Diffusion Transformers (DiTs) have become the dominant architecture for image and video generation, creating growing demand for efficient DiT

arXiv:2607.01409v1 Announce Type: cross Abstract: GPU training jobs fail often, roughly two in five on large production clusters, yet the operator typically learns of a failure only by reconnecting ho

arXiv:2607.02092v1 Announce Type: cross Abstract: Flow-matching vision-language-action policies generate robot action chunks through an iterative transport process, creating an opportunity for test-ti

arXiv:2601.02813v3 Announce Type: replace Abstract: Aligning language models to qualitative behavioral traits, such as human-likeness, remains difficult because they are hard to define, measure, and o