Search: “evaluation”

arXiv:2610.02788v1 Announce Type: new Abstract: Transferring robotic skills from simulation to reality requires task knowledge that remains usable across differences in perception, dynamics, and embod

arXiv:2610.02953v1 Announce Type: new Abstract: Long-context LLM serving is increasingly bottlenecked by KV-cache memory, especially in resource-constrained scenarios. Among existing KV-cache compress

arXiv:2610.02386v1 Announce Type: cross Abstract: We present a comprehensive overview of the challenges and opportunities in social bot detection in the context of the rise of sophisticated AI-based c

arXiv:2610.02360v1 Announce Type: new Abstract: Vision-language-action (VLA) policies enable diverse robotic manipulation but can fail during execution without recognizing their own errors. Human obse

arXiv:2610.03029v1 Announce Type: new Abstract: Gene set analysis is a cornerstone of functional genomics, yet it remains labor-intensive and heavily dependent on manual curation and expert biological

arXiv:2610.02338v1 Announce Type: cross Abstract: A growing body of work suggests that tactile sensing gives robot policies contact information that complements vision in dexterous manipulation. Howev

arXiv:2610.03195v1 Announce Type: new Abstract: As LLM agents decide on users' behalf which product to buy, which hotel to book, or which paper to cite, a preference for items from certain sources (th

arXiv:2610.02726v1 Announce Type: new Abstract: Flow-matching-based multi-view world models generate realistic videos, but are commonly restricted to fixed camera rigs. Extending them to continuously

arXiv:2610.03124v1 Announce Type: cross Abstract: Open-weight language models can be downloaded, modified, and deployed beyond their developers' control, limiting the effectiveness of centrally enforc

arXiv:2610.02225v1 Announce Type: new Abstract: While corporate sustainability mandates are expanding, the systemic reliance on self-reported emissions data exposes financial markets to pervasive gree

arXiv:2610.02383v1 Announce Type: cross Abstract: Looped Transformers apply the same layers several times per token, adding compute to improve quality without more parameters. Each recursion, however,

arXiv:2610.02839v1 Announce Type: cross Abstract: We show that the causality of language models (LMs) may not be necessary nor optimal. This is the case when system behavior (denoted as S) is incorpor

arXiv:2610.02247v1 Announce Type: cross Abstract: Artificial intelligence increasingly serves as a natural-language interface to complex technical systems, letting people accomplish sophisticated task

arXiv:2610.03213v1 Announce Type: new Abstract: Tool-equipped AI agents use tool calls to access data and act on external systems. Horizontal growth of agentic systems increases the number of these in

arXiv:2610.03128v1 Announce Type: new Abstract: Quantitative trading strategy design aims to discover trading programs from historical data that remain effective in future markets, which can be viewed

arXiv:2610.03693v1 Announce Type: new Abstract: Scarcity of labeled data limits development of deep learning biomarkers in oncology. We develop a two-stage AI model predicting pathological complete re

arXiv:2601.15906v2 Announce Type: replace Abstract: Despite rapid progress in multimodal affective foundation models, how affective capabilities emerge within their internal architectures remains poor

arXiv:2610.03077v1 Announce Type: new Abstract: Propaganda detection is an essential task in natural language processing (NLP), particularly in the context of manipulative political communications. Ho

arXiv:2610.03221v1 Announce Type: new Abstract: Video creation spans text-to-video (T2V), image-to-video (I2V), and condition-based generation, yet video diffusion models remain costly because they re

arXiv:2610.02616v1 Announce Type: new Abstract: Harness evolution improves an LLM agent's prompts, tools, and workflow, while the optimizer's own tools and procedures often remain fixed. We study whet

arXiv:2610.02801v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) achieves strong sample efficiency by planning within learned latent dynamics, yet its performance degrades sub

arXiv:2610.02713v1 Announce Type: new Abstract: Most KV-cache compression methods classify attention heads once, either offline or during prefill, and keep this classification fixed throughout generat

Watermarks have limits. They’re often undetectable, especially in short passages. Rewriting or translating text can completely remove the watermark. That’s why, for now, only approved researchers will

arXiv:2610.03036v1 Announce Type: cross Abstract: We present WebFovea, a vision-based web agent that placed 2nd in the WebRetriever Challenge 2026 with a final score of 57.0 out of 100. The challenge

arXiv:2610.02614v1 Announce Type: new Abstract: AI models serving a heterogeneous population must act on the principles appropriate to each user and context. While post-training has been shown to narr

arXiv:2610.03713v1 Announce Type: cross Abstract: Continual learning treats degradation on previously seen data as evidence of failure, a convention inherited from settings with a stationary predictio

arXiv:2610.03598v1 Announce Type: cross Abstract: Reinforcement learning (RL) is increasingly used for financial optimal-control problems when complex dynamics make analytical strategies difficult to

arXiv:2511.12749v3 Announce Type: replace-cross Abstract: Forecasting many sparse series requires two choices: how much of each series' own past to retain, and how much to borrow from other series. We

arXiv:2610.03057v1 Announce Type: new Abstract: Relational foundation models are increasingly pretrained on synthetic databases, yet downstream benchmarks reveal little about why one synthetic corpus

arXiv:2610.03465v1 Announce Type: cross Abstract: K-fold cross-validation (CV) is widely used as evidence of out-of-sample performance, although folds are neither independent experiments nor equally i

arXiv:2610.02405v1 Announce Type: new Abstract: Using a frontier model like Claude Opus as a meta-agent to generate terminal tasks and verifiers for RL training is increasingly common. Yet a runnable

arXiv:2610.03068v1 Announce Type: new Abstract: Understanding compositional failures in text-to-image diffusion requires identifying both where stress is detectable and how intervention changes the ou

arXiv:2610.02694v1 Announce Type: new Abstract: Future planetary surface missions are likely to involve multiple independently operated rovers sharing the same deployment region, raising the need to v

arXiv:2610.02468v1 Announce Type: cross Abstract: We present Windfoil, a GPU-friendly algorithm that treats rasterisation and differentiable vector graphics as two sides of the same problem by evaluat

arXiv:2610.02508v1 Announce Type: new Abstract: World action models (WAMs) have emerged as a promising paradigm for robotic control by jointly predicting future visual dynamics and actions from an ini

arXiv:2610.03567v1 Announce Type: new Abstract: We describe the Writerslogic team's participation in the CLEF 2026 SimpleText shared task, addressing Task 1 (text simplification) and Task 2 (complexit

arXiv:2610.02263v1 Announce Type: cross Abstract: Patient-level lung ultrasound (LUS) diagnosis requires integrating findings acquired across multiple anatomical zones, yet clinical examinations frequ

arXiv:2610.03087v1 Announce Type: cross Abstract: Deterministic data loading is important for foundation model development: model researchers need confidence that differences they observe across costl

Grok 4.7 is #1 on the AA Cyber Index Grok 4.7 xHigh ranked #1 on Artificial Analysis’ Cyber Index Grok 4.7 is now very powerful with serious cybersecurity capabilities It outperformed Claude Opus 5.5,

if you’re building an ai app, you might want to host inference to improve your margins, and if you do that you should support a few models, and if you’re doing that you might as well build a router, a

😂 you might call this ... slippery slop if you’re building an ai app, you might want to host inference to improve your margins, and if you do that you should support a few models, and if you’re doing

ggml-openvino: update to 2026.4.1, optimize performance, expand ops, improve device listing. (#29852) ggml-openvino : Qwen3.5 MoE perf (#312) Squash of ravi9#312: ggml-openvino: add detailed inference

LWiAI Podcast #258 (recorded 26‑Sep‑2026) reviews major AI updates from the previous week. Key developments include Anthropic’s Opus 5.5 release—offering lower pricing, faster performance and robust b

Reasoning from scratch, round number 6! An introduction (and implementation) of Reinforcement Learning with Verifiable Rewards (RLVR) and Group Relative Policy Optimization (GRPO). 00:00 Introduction

arXiv:2610.02160v1 Announce Type: new Abstract: Precise control over camera and object motion is essential for professional video production. Existing methods control objects only coarsely, through im

arXiv:2512.06205v3 Announce Type: replace Abstract: The symbol grounding problem asks how a token such as cat can be about cats. We propose a framework for auditing grounding claims against a declared