Search: “evaluation”

The specific tweet from @0xSero is not directly accessible, and the search results don't surface the exact model or event being referenced in that post. However, based on the context clues in the t...

The referenced tweet (from @himanshustwts) is not publicly accessible without a login, so its exact content cannot be retrieved. However, based on contextual search results, this post appears to be...

Enterprises are rapidly moving AI workloads from experimentation to production on Google Kubernetes Engine (GKE), using its scalability to serve powerful inference endpoints. However, as these models

The DAIR.AI post references a Claude Code Cheat Sheet consolidating key commands, shortcuts, and best practices for Anthropic's terminal-based agentic coding tool. Claude Code is Anthropic's AI-po...

Tesla V14.3 self-driving review. The point releases will bring polish. V15 will far exceed human levels of safety, even in completely unsupervised and complex situations. 600 miles in with FSD v14.3 a

Anthropic announced it has grown its ARR from $19B to $30B in just one month, coinciding with the formal unveiling of Claude Mythos Preview — described in leaked company documents as 'by far the m...

I ran five coding tasks against nine models on one RX 9060 XT (16 GB). Each run gets a single spec file in an empty directory and has to produce solution.py and test_solution.py, run its own tests, an

Great paper from NVIDIA sharing an open midtraining recipe for agentic coding. NVIDIA kept SFT identical and added one midtraining stage. SWE-bench Multilingual went from 55.8 to 62.8 on Nemotron 3.5

European 78B A3.4B model is now supported by llama.cpp, I am waiting for some GGUFs https://huggingface.co/Aleph-Alpha/Kolibri-1 Kolibri is Aleph Alpha's mixture-of-experts (MoE) reasoning model, with

Reasoning From Scratch round 8, the finale! This last lecture in the series covers distillation as an efficient alternative to the previous reinforcement learning training runs. (Planning to take a br

arXiv:2603.13049v3 Announce Type: replace Abstract: Global numerical weather prediction (NWP) and artificial intelligence (AI) models often underestimate tropical cyclone (TC) intensity, partly becaus

arXiv:2610.21353v1 Announce Type: new Abstract: Accurate localization is critical for a wide range of applications, including navigation, augmented reality, safety management, and healthcare. However,

arXiv:2603.25370v2 Announce Type: replace-cross Abstract: Probabilistic forecasts provide a principled representation of forecast uncertainty through predictive distributions. Directly propagating pre

arXiv:2610.21238v1 Announce Type: new Abstract: A few well-annotated datasets for land-cover semantic segmentation have recently been introduced to advance the field of earth observation technologies.

arXiv:2610.20630v1 Announce Type: new Abstract: The development of Financial Natural Language Processing (NLP) systems for Brazilian Portuguese is hindered by the scarcity of domain-specific datasets.

arXiv:2610.20921v1 Announce Type: new Abstract: Most debate about releasing capable AI systems treats the choice as binary: keep the model behind an API, or publish the weights. That framing runs toge

arXiv:2610.21323v1 Announce Type: new Abstract: Most vision-language models (VLMs) treat the vision encoder as a static feature extractor: it encodes an image once, independently of the question, and

arXiv:2610.21177v1 Announce Type: new Abstract: Task completion alone does not determine whether a stateful agent satisfied its obligations, and a recorded judgment does not guarantee that its support

arXiv:2508.02276v3 Announce Type: replace-cross Abstract: Autonomous agents, from virtual laboratories to biological data-analysis agents and co-scientists, have begun to turn scientific goals into hy

arXiv:2512.02004v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) encode factual knowledge within hidden parametric spaces that are difficult to inspect or control. While Sparse A

arXiv:2610.21211v1 Announce Type: new Abstract: Proactive robots should anticipate user needs and provide assistance before being explicitly asked. A straightforward approach is to infer human intenti

The tweet from @NousResearch links to a Windows Central article written by Zac Bowden that provides an in‑depth review and benchmark analysis of Nvidia’s RTX Spark. Posted on Oct 16, 2026, the review

arXiv:2610.21882v1 Announce Type: cross Abstract: Embodied spatial intelligence requires more than visual recognition: models must localize entities, reason about their relations, and express this kno

arXiv:2610.21164v1 Announce Type: new Abstract: Dementia severely impairs communication abilities and turns everyday conversations into challenging experiences. Individuals affected by dementia freque

arXiv:2610.21218v1 Announce Type: new Abstract: Agentic large language models have been documented to lose reasoning capability when placed inside a harness, the software that mediates their observati

arXiv:2610.21060v1 Announce Type: cross Abstract: To address sparse terminal rewards in LLM arithmetic reasoning, we propose a Bellman-consistent trajectory RL method. Our framework introduces Traject

arXiv:2610.21760v1 Announce Type: new Abstract: As image generation models become increasingly capable of producing highly realistic content, traditional forensic techniques are struggling to keep up.

arXiv:2610.21403v1 Announce Type: new Abstract: Distribution shifts pose a fundamental challenge to robust multimodal learning. Existing methods typically promote invariance by suppressing environment

arXiv:2610.21184v1 Announce Type: new Abstract: Multi-hop retrieval-augmented generation (RAG) requires an agent to retrieve evidence for a sequence of dependent sub-questions. When a wrong answer lac

arXiv:2610.20794v1 Announce Type: new Abstract: Recent reinforcement learning approaches have improved visual text generation, yet generated images still suffer from incorrect wording and malformed gl

arXiv:2610.21383v1 Announce Type: new Abstract: Block Influence (BI) ranks Transformer blocks for depth pruning from their input-output cosine change, but the ranking depends on the calibration distri

arXiv:2610.21294v1 Announce Type: new Abstract: Transformer-based language models have shown strong capabilities across many tasks and domains. However, prior work shows that, for a given task, not al

arXiv:2610.21006v1 Announce Type: new Abstract: To use language models to help us make decisions we would like to understand the rationale behind the language model's outputs. In principle, the langua

arXiv:2511.16221v2 Announce Type: replace-cross Abstract: Despite their advanced reasoning capabilities, state-of-the-art Multimodal Large Language Models (MLLMs) still lack a core component of human

arXiv:2610.21095v1 Announce Type: new Abstract: World and action modeling are closely related, yet their reciprocal benefits under unified causal training remain unclear. We introduce OneWM, a simple

arXiv:2610.21151v1 Announce Type: cross Abstract: Cybersecurity interviews uncover critical security experiences, behaviors, and privacy concerns often not fully captured by conventional technical ass

arXiv:2610.20668v1 Announce Type: cross Abstract: We introduce CascadeLedger, a counterfactual execution-audit framework for budgeted language-model cascades. The protocol enforces call-before-read se

arXiv:2610.22292v1 Announce Type: cross Abstract: Large language models (LLMs) are becoming prevalent in scenarios where honesty is critical. However, despite alignment training, these models still ex

arXiv:2610.20750v1 Announce Type: new Abstract: Vision-language-action (VLA) models are a promising approach to general purpose robot manipulation. While the internal computation of vision-language mo

arXiv:2610.22126v1 Announce Type: cross Abstract: Existing feature attribution methods that account for feature dependencies do not scale to high dimensions. We propose causal integrated gradients (CI

arXiv:2607.18921v2 Announce Type: replace-cross Abstract: Circuit extraction identifies model components whose presence preserves a target behavior under ablation, but preserving behavior does not sin

arXiv:2610.21409v1 Announce Type: new Abstract: Traditional keypoint descriptors, such as SIFT (Scale-Invariant Feature Transform) and ORB (Oriented FAST and Rotated BRIEF), are computed from local im

arXiv:2610.21804v1 Announce Type: new Abstract: Incremental learning (IL) aims to continually acquire new knowledge (plasticity) while retaining previously learned information (stability). However, st

arXiv:2610.21364v1 Announce Type: new Abstract: One-shot Font Generation (OFG) aims to synthesize a target glyph by transferring the stylistic characteristics of a single reference glyph while preserv

arXiv:2610.20877v1 Announce Type: cross Abstract: Early detection of mild cognitive impairment remains a critical bottleneck in dementia care, demanding scalable tools capable of capturing subtle beha

arXiv:2610.21126v1 Announce Type: new Abstract: Sparse KV compression reduces long-context inference costs by retaining selected historical states, yet these states typically keep their coordinates fr