Search: “benchmark”

arXiv:2609.33264v1 Announce Type: new Abstract: Video world models are emerging as data engines, action planners, and generative simulators for autonomous driving, but existing benchmarks primarily as

We let open models access the outside world during evals on tasks from public benchmarks. Here's what happened: Most went and found upstream commits containing fixes for the tasks they were supposed t

Utkarsh Shetti / Reuters: AI agent startup Instinct raised a 1B Series C from Sequoia, Benchmark, and Coatue at a 10B valuation and details recent products, such as a concierge service — AI agent firm

arXiv:2609.31082v1 Announce Type: new Abstract: Knowing where species occur is fundamental for biodiversity research and conservation. Species distribution models (SDMs) link species observations to e

Model personality matters in a way that benchmarks can't capture. Opus models went through a rough patch from around 4.7 to 5 where they just didn't feel 'Claude-y' anymore, more like an watered-down

arXiv:2609.29669v1 Announce Type: cross Abstract: Robot learning now advances along two tracks that rarely meet. On one side, direct Vision-Language-Action (VLA) policies map observations to actions a

arXiv:2609.28575v1 Announce Type: new Abstract: Long-conversation memory benchmarks increasingly test recall and prompted knowledge updates, and recent work studies evolving user beliefs and memory st

arXiv:2507.00938v4 Announce Type: replace-cross Abstract: Foundation models now enable autonomous agents to interact with real-world websites, but existing benchmarks emphasize general-purpose browsin

arXiv:2609.26809v1 Announce Type: new Abstract: Reliable agricultural yield statistics are typically reported at coarse administrative scales, whereas modern geospatial machine learning methods requir

arXiv:2609.28449v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in coding tasks, but their ability to reason about code execution remains unclear. Existing reposit

arXiv:2609.23201v1 Announce Type: new Abstract: Benchmark scores increasingly influence the development, marketing, and selection of large language models (LLMs). Yet an overall score is interpretable

arXiv:2602.18307v2 Announce Type: replace-cross Abstract: Large language models have achieved striking results in interactive theorem proving, particularly in Lean. However, most benchmarks for LLM-ba

arXiv:2609.24124v1 Announce Type: new Abstract: Active perception and manipulation are crucial for robots to interact with complex scenes. Existing benchmarks struggle to evaluate how robots effective

arXiv:2609.23490v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly execute multi-step workflows through tool use and interaction with users and environments. However, curre

arXiv:2609.23067v1 Announce Type: new Abstract: Referring surgical video instrument segmentation (RSVIS) aims at segmenting the instrument in a surgical video, given a textual description. Despite rec

arXiv:2609.23003v1 Announce Type: new Abstract: We present M3GA-Wild, the first benchmark for multi-modal, multi-session ground-to-aerial place recognition in forests. M3GA-Wild unifies and extends ex

arXiv:2609.22220v1 Announce Type: new Abstract: Benchmarks for LLM-generated GPU kernels decide correctness with a few random inputs and a loose floating-point tolerance, and their verdicts now feed l

arXiv:2609.23055v1 Announce Type: new Abstract: Discrete diffusion models now match autoregressive language models on several benchmarks, while the question of how best to train them has received far

arXiv:2609.24613v1 Announce Type: cross Abstract: Prior case retrieval (PCR) aims to identify precedent cases relevant to a given query case. Existing PCR benchmarks and methods predominantly operate

arXiv:2609.22038v1 Announce Type: new Abstract: We introduce QuranicMMLU, a benchmark for evaluating generative AI on Quranic Arabic across multiple dimensions of linguistic complexity. Existing Quran

arXiv:2508.06734v3 Announce Type: replace-cross Abstract: While graph-based Android malware classifiers report strong benchmark accuracy of over 94%, their performance sharply decreases up to 45% when

arXiv:2609.19154v1 Announce Type: new Abstract: While Large Language Models (LLMs) achieve high accuracy on established Classical Chinese Poetry benchmarks, it remains challenging to distinguish trans

We just released the first version of our Creative Writing benchmark, comparing 24 LLMs against human writers across 475 writing prompts. Creative writing is subjective, so the rankings aren't meant t

arXiv:2603.28662v2 Announce Type: replace-cross Abstract: Agentic vision-language models increasingly act through extended interactions, but most evaluations still focus on single-image, single-turn c

arXiv:2603.03884v2 Announce Type: replace-cross Abstract: Topic localization aims to identify spans of text that express a given topic defined by a name and description. To study this task, we introdu

arXiv:2603.09908v2 Announce Type: replace Abstract: Existing aerial-robotics benchmarks target vehicles from hundreds of grams to several kilograms and typically expose only high-level state data. The

arXiv:2505.23126v5 Announce Type: replace Abstract: Although many benchmarks evaluate the reasoning abilities of Large Language Models (LLMs) within domains such as mathematics, coding, or data wrangl

arXiv:2609.18396v1 Announce Type: cross Abstract: Virtual sensing, the estimation of hard-to-measure quantities from available sensor measurements, is a critical enabler for control and monitoring in

arXiv:2609.17985v1 Announce Type: new Abstract: AI agents are usually evaluated by whether they complete a task. In interactive service settings, a successful agent can still frustrate users by asking

arXiv:2609.18949v1 Announce Type: cross Abstract: We introduce StableEval Arena, a cost-aware benchmark framework for evaluating agentic AI systems on stablecoin peg-risk prediction. StableEval Arena

arXiv:2601.18493v2 Announce Type: replace Abstract: Vision--language models (VLMs) show promise for disaster-response remote sensing, but existing benchmarks mainly emphasize scene-level or damage-cen

arXiv:2603.12264v2 Announce Type: replace Abstract: Unified multimodal models target joint understanding, reasoning, and generation, but current image editing benchmarks are largely confined to natura

arXiv:2603.14456v2 Announce Type: replace Abstract: Persian poses unique audio understanding challenges through its classical poetry, traditional music, and pervasive code-switching, none of which is

TensorRT Edge‑LLM ran Qwen 3.6‑27B on a single NVIDIA Jetson AGX Thor and completed the MLPerf Edge Agentic benchmark in 24 min 36 s—52.33 tokens/s—which is 6.4× faster than the llama.cpp reference (2

arXiv:2609.16486v1 Announce Type: new Abstract: Rapid advancements in vision-language models have propelled Referring Remote Sensing Image Segmentation (RRSIS) to the forefront of Earth observation. H

EDIT: Sorry for the unclear title. This model is UkisAI's Swift-Qwen3.8-27B, not a new version of BottleCap AI's 3.6-ThinkingCap. All credit goes to UkisAI for making great fine-tune, and I made this

arXiv:2512.24565v4 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly serving as autonomous agents, and their utilization of external tools via the Model Context Protocol (

arXiv:2609.14473v1 Announce Type: new Abstract: Personal AI assistants hold the potential to evolve from digital interfaces into embodied companions capable of guiding users through complex physical a

Some food for thought when designing benchmarks... So, here's a little computer-use (visual) comparison between GPT-5.6 Astra and Qwen3.8 Max. The task here was to recreate the image in the center usi

arXiv:2609.12350v1 Announce Type: new Abstract: Close-range first-person field images are important for mobile maize phenotyping because many plant-level traits depend on in-canopy structures that are

arXiv:2609.13003v1 Announce Type: new Abstract: Binary-choice truth benchmarks ask models to choose between a correct and an incorrect answer, but if the two answers differ systematically in surface-l

arXiv:2609.12884v1 Announce Type: new Abstract: A medical claim's correctness often depends not on the claim alone, but on the clinical structure around it. A claim may require a lab reference range,

arXiv:2512.14691v3 Announce Type: replace Abstract: Modern multimodal generative models can synthesize visually compelling images and videos, but it remains unclear whether this visual fluency reflect

arXiv:2609.12345v1 Announce Type: new Abstract: Existing agent benchmarks mainly evaluate final task success or tool-call correctness, providing limited insight into whether agents can reliably diagno

A few people here mentioned interest in a way to test their custom Pi setups, so I figured I’d drop this here: RoastMyHarness The basic idea is a small engine that sets up an environment to run DeepSW

arXiv:2609.11234v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in peer review at major AI conferences, yet novelty remains a persistent weak point. Existing benchma