Search: “tools”

arXiv:2605.30188v1 Announce Type: cross Abstract: Reliable probability estimates are critical in many machine learning applications, yet modern classifiers are often poorly calibrated. Post-hoc calibr

arXiv:2603.01311v2 Announce Type: replace Abstract: The discovery of novel catalysts tailored for particular applications is a major challenge for the twenty-first century. Traditional methods for thi

ChatGPT diagnosed 40 million people with a disease that was invented as a joke. Not a real disease. Not a misunderstood disease. A completely fictional condition with a fake name, fake papers, and fak

arXiv:2605.29277v1 Announce Type: cross Abstract: We present Code-QA-Bench, a fully automated framework for synthesizing repository-level code understanding benchmarks that separates genuine code comp

arXiv:2602.20176v2 Announce Type: replace-cross Abstract: D-peptide binders targeting L-proteins have promising therapeutic potential. Despite rapid advances in machine learning-based target-condition

arXiv:2605.29615v1 Announce Type: cross Abstract: Vision-language models (VLMs) have made strong progress on high-level image-text alignment, yet their ability to perceive subtle visual differences re

arXiv:2605.30275v1 Announce Type: new Abstract: Earlier detection of pancreatic cancer is key to enabling wider access to curative treatment and reducing cancer deaths; however, screening is presently

arXiv:2605.30169v1 Announce Type: cross Abstract: As autonomous language model agents proliferate, forming an emerging agentic web with real-world consequences, what credibility signals can you use to

arXiv:2602.22045v2 Announce Type: replace Abstract: We introduce DLT-Corpus, the largest domain-specific text collection for Distributed Ledger Technology (DLT) research to date: 2.98 billion tokens f

arXiv:2602.08783v3 Announce Type: replace Abstract: Latent or continuous chain-of-thought methods replace explicit textual rationales with a number of internal latent steps, but these intermediate com

arXiv:2511.11703v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) in 3D environments with high-dimensional sensory input poses two major challenges: (1) the high memory consumption

arXiv:2605.29630v1 Announce Type: cross Abstract: End-to-end agent-memory benchmarks report a single hit@k per retriever, confounding lexical leakage (uncontrolled query/gold/distractor entity overlap

arXiv:2509.22504v3 Announce Type: replace Abstract: As language model (LM) agents become increasingly capable and adopted in real-world applications, there is a growing need for scalable evaluation fr

arXiv:2505.20634v2 Announce Type: replace Abstract: Concept shift occurs when the distribution of labels conditioned on the features changes between domains, which can make even a well-tuned ML model

arXiv:2605.29955v1 Announce Type: new Abstract: We present AutoformBot, a multi-agent system for building an Autoformalized Textbook Library At Scale (Atlas) in Lean 4. AutoformBot orchestrates thousa

Many organizations’ single source of truth is data that resides in BigQuery, Google’s governed, secure and petabyte-scale data platform. However, the 'last mile' of ad-hoc analysis, modeling, and repo

arXiv:2605.28965v1 Announce Type: new Abstract: Linking free-text phenotype descriptions to ontology terms, typically referred to as phenotype annotation, is essential for the cross-study integration

arXiv:2605.29816v1 Announce Type: new Abstract: The work presents an approach for addressing the challenge of robustness in Large Language Models (LLMs) to alterations and potential errors caused by s

I don't have current information about this specific Reddit discussion or the installation process for WAN 2.2 into Forge Neo. This appears to be a technical support question from the StableDiffusion

A developer created an open-source GUI application with a brutalist design for interacting with Ollama models and the Personal Iris (PI) platform. The application is compatible with both ARM64 and Int

This post from LangChain's Harrison Chase contrasts traditional manual methods of improving AI agents (tracing execution, identifying patterns, writing evaluations, and implementing fixes) with a more

arXiv:2605.30002v1 Announce Type: new Abstract: Cross-domain multimodal time series forecasting is a challenging task, requiring models to integrate precise numerical comprehension, cross-domain seman

arXiv:2605.30245v1 Announce Type: new Abstract: Current plan-based reasoning methods improve large language models (LLMs) by inserting a planning stage before execution, giving rise to the question ri

arXiv:2502.07623v4 Announce Type: replace Abstract: After developing a computational system for morphological analysis of the Mapuche language, and evaluating it with texts from various authors and st

llama.cpp now has an official website: https://llama.app Our goal is to make local AI accessible to everyone, and improving the user experience is a big part of that. On the new landing page you’ll fi

arXiv:2605.29798v1 Announce Type: new Abstract: Reliable identification of fracture origins in alumina matrix composite hip and knee implants is critical for quality assurance and patient safety, yet

arXiv:2605.28825v1 Announce Type: new Abstract: Large language models (LLMs) frequently encode factual and reasoning knowledge in their internal representations that is not faithfully reflected in the

arXiv:2605.29965v1 Announce Type: new Abstract: The development of temporal extensions of Answer Set Programming (ASP) has led to the emergence of non-monotonic linear-time (TEL), dynamic (DEL), and m

arXiv:2605.29475v1 Announce Type: cross Abstract: Large language models (LLMs) show remarkable potential in scientific hypothesis discovery. However, existing approaches face two critical limitations:

arXiv:2605.29220v1 Announce Type: new Abstract: Tracking the dynamics of non-canonical biological systems in microscopy videos remains a persistent challenge. Both classical and learning-based tracker

Liquid AI released LFM2.5-8B-A1B, a device-optimized model designed to power real-life applications on phones, laptops, PCs, robots, and lightweight server-side use-cases. The model is a fast, memory-

arXiv:2605.29357v1 Announce Type: new Abstract: Modern tensor compilers such as TorchInductor deliver substantial speedups on mainstream models, yet face a systematic performance ceiling on long-tail

arXiv:2506.06254v2 Announce Type: replace Abstract: Large Language Model (LLM) empowered agents have recently emerged as advanced paradigms that exhibit impressive capabilities in a wide range of doma

arXiv:2605.29815v1 Announce Type: new Abstract: The growing number of submitted papers has motivated the exploration of Large Language Models (LLMs) as a means to support and augment the peer review p

Production traffic from frontier models is a golden data asset. If you can efficiently mine the traces, filter for quality, and fine-tune smaller models on them, you get specialized performance at a f

quick, name a prominent company that achieved a major win via tokenmaxxing! I've yet to see, or hear of a company that is winning against its competition, because said company is spending more on AI t

arXiv:2602.02909v2 Announce Type: replace Abstract: Inference-time scaling via chain-of-thought (CoT) reasoning is a major driver of state-of-the-art LLM performance, but it comes with substantial lat

arXiv:2603.05488v4 Announce Type: replace-cross Abstract: We provide evidence of performative chain-of-thought (CoT) in reasoning models, where a model becomes strongly confident in its final answer,

arXiv:2601.22139v2 Announce Type: replace-cross Abstract: Reasoning-oriented Large Language Models (LLMs) have achieved remarkable progress with Chain-of-Thought (CoT) prompting, yet they remain funda

arXiv:2605.30326v1 Announce Type: cross Abstract: The ability to reason, adapt, and creatively solve problems under unexpected challenges is essential for robots operating in real-world environments.

arXiv:2605.30345v1 Announce Type: new Abstract: Printed circuit board (PCB) schematic design defines nearly all electronic hardware, but it remains manual and expertise-intensive. While generative AI

arXiv:2605.30104v1 Announce Type: new Abstract: Widely used language-model benchmarks are increasingly saturated, with frontier systems often receiving near-tied scores that standard metrics cannot re

arXiv:2507.06092v4 Announce Type: replace-cross Abstract: Machine learning-based supervised classifiers are widely used for security tasks, and their improvement has been largely focused on algorithmi

arXiv:2601.11178v2 Announce Type: replace Abstract: Social media platforms are increasingly dominated by long-form multimodal content, where harmful narratives are constructed through a complex interp

arXiv:2605.30036v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate a remarkable capacity to adopt different personas and roles; however, it remains unclear whether they can manif

This is a diary entry to myself, so I remember what AI was like today. It's just going to be a bullet-list stream of consciousness. - There are still so many leaders that have never seen an agent run