While model and agent evaluation are inextricably linked, their technical benchmarks and metrics for success are fundamentally different.
Mastering Agentic Techniques: AI Agent Evaluation | NVIDIA Technical Blog…By incorporating simulated trajectories into our evaluation pipeline, we were able to reduce variance in key real-world metrics by up to 83%, enabling faster and more confident model assessments. Secondly, we…
AMD Instinct™ GPUs on Vultr Cloud Available Without the Wait Request Evaluation The Everywhere Cloud Vultr stands out as the cloud platform purpose-built for innovation. Unlike hyperscalers weighed down by complexity…
…by Sajib Acharjee Dip on May 12 Virginia Polytechnic Institute and State University Authors: , , Abstract PlantMarkerBench presents a multi-species benchmark for evaluating literature-based plant marker evidence interpretation, assessing models on…
…The model under consideration resembles the UK's approach, where the AI Security Institute evaluates frontier models against safety benchmarks before deployment. Per security publication CSO Online , both the UK’s AISI…
Two years ago we released VQAScore: ask a VLM "does this image show {prompt}?" and use P(Yes) as the score. It became a go-to evaluation metric and reward model for image generation, replacing CLIPScore across the field …
Current LLM benchmarks are broken. We think long horizon "world" building could be an interesting additional way to evaluate LLMs, since it combines many aspects such as need for advanced reasoning, tool calling, working…
I built AptSelect to stop writing throwaway scripts every time I needed to test how different LLMs handle specific instructions and prompt edge cases.What it does:Parallel Execution: Send a single prompt to OpenAI, Anthr…
I'm excited to announce Elmo, an MIT-licensed, open source AEO/GEO tool.We help you scrape ChatGPT/Google AI Mode/etc using web scrapers like BrightData/Olostep/etc, evaluate prompts against the OpenAI/Anthropic/Mistral …
TLDR: Forked pytorch and triton internals . Changed attention so its linear first layer , middle quadratic layer, last linear layer Inference got much faster with a low perplexity hit in tests .Full attention O(n²): 17.9…
…Experiments across lexical, general-purpose, and reasoning-intensive retrievers show that aspect-aware and agentic evaluation expose behaviors hidden by standard metrics, while RTriever-4B substantially improves over its base model. View…
…SOC 2, ISO 27001 & 42001, and GDPR-aligned controls, plus a growing network of data centers across North America and Europe connected by a private backbone. Evaluate AMD Instinct GPUs on Crusoe…
…A Platform for Prompt Injection Evaluation (2026) Claudini: Autoresearch Discovers State-of-the-Art Adversarial Attack Algorithms for LLMs (2026) Transient Turn Injection: Exposing Stateless Multi-Turn Vulnerabilities in Large Language Models…
…We further provide Workspace-Bench-Lite, a 100-task subset that preserves the benchmark distribution while reducing evaluation costs by about 70%. We evaluate 4 popular agent harnesses and 7 foundation models…
…Surgical-Simulator advances research by generating realistic surgical robotics data for policy training and evaluation. By learning directly from real surgical data rather than hand-engineered physics models, it helps reduce the…
…Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks? Published on Jun 3 Submitted by taesiri on Jun 4 Authors: , , , Dongfu Jiang , , Hang Hua , , , , Lichi Li , , , , , , , , , Abstract AutoLab benchmark evaluates…