Search: “models”

arXiv:2604.21481v1 Announce Type: new Abstract: Crowdsourced pairwise evaluation has emerged as a scalable approach for assessing foundation models. However, applying it to Text to Speech(TTS) introdu

arXiv:2604.21098v1 Announce Type: new Abstract: Motivated by loss of control risks from misaligned AI systems, we develop and apply methods for measuring language models' propensity for unsanctioned b

arXiv:2604.21249v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) enable high-level semantic reasoning for end-to-end autonomous driving, particularly in unstructured environments, e

arXiv:2604.20904v1 Announce Type: cross Abstract: Information handling practices of LLM agents are broadly misaligned with the contextual privacy expectations of their users. Contextual Integrity (CI)

I cannot provide an accurate summary for this entry as the text appears incomplete and lacks sufficient context. The post fragment references o3 (likely an AI model), GPT-5.5, and discusses timeline/e

arXiv:2604.20937v1 Announce Type: new Abstract: Video Large Language Models (Video LLMs) incur high inference latency due to a large number of visual tokens provided to LLMs. To address this, training

arXiv:2604.21356v1 Announce Type: new Abstract: High-quality digital terrain models derived from airborne laser scanning (ALS) data are essential for a wide range of geospatial analyses, and their gen

arXiv:2604.21282v1 Announce Type: cross Abstract: Automated code vulnerability detection is critical for software security, yet existing approaches face a fundamental trade-off between detection accur

This analysis examines the token consumption and economics of coding assistants, likely comparing different AI models' efficiency and cost-effectiveness for code generation tasks. The piece probably d

arXiv:2604.20874v1 Announce Type: cross Abstract: Every system that maintains a large language model conversation beyond a single session faces two inescapable constraints: the context window is finit

arXiv:2604.21057v1 Announce Type: new Abstract: The field of Language Reasoning Models (LRMs) has been very active over the past few years with advances in training and inference techniques enabling L

arXiv:2604.21657v1 Announce Type: new Abstract: Machine learning methods that predict initial guesses from molecular geometry can reduce this cost, but matrix-prediction models fail when extrapolating

arXiv:2511.13587v2 Announce Type: replace-cross Abstract: Visual autoregressive (AR) generation models have demonstrated strong potential for image generation, yet their next-token-prediction paradigm

We benchmarked GPT-5.5 on document understanding 📄📊 We ran it through ParseBench, our comprehensive OCR benchmark over enterprise documents. We evaluated metrics across various dimensions: visual grou

arXiv:2511.01458v2 Announce Type: replace-cross Abstract: Safety and reliability are critical for deploying visual question answering (VQA) systems in surgery, where incorrect or ambiguous responses c

arXiv:2505.11336v4 Announce Type: replace Abstract: Despite the growing adoption of large language models (LLMs) in academic workflows, their capabilities remain limited in supporting high-quality sci

arXiv:2602.00208v2 Announce Type: replace-cross Abstract: Unsupervised anomaly detection is a challenging problem due to the diversity of data distributions and the lack of labels. Ensemble methods ar

OpenAI's API pricing structure charges 5 per 1 million input tokens and 30 per 1 million output tokens, with support for a 1 million token context window. This pricing model reflects the higher cost o

arXiv:2604.20795v1 Announce Type: new Abstract: This paper presents a hybrid architecture for intelligent systems in which large language models (LLMs) are extended with an external ontological memory

arXiv:2512.15146v3 Announce Type: replace Abstract: Test-time reinforcement learning mitigates the reliance on annotated data by using majority voting results as pseudo-labels, emerging as a complemen

arXiv:2604.19984v1 Announce Type: cross Abstract: Research has documented LLMs' name-based bias in hiring and salary recommendations. In this paper, we instead consider a setting where LLMs generate c

arXiv:2604.20348v1 Announce Type: cross Abstract: Language Models (LLMs) have emerged as powerful reasoning engines for embodied control. In particular, In-Context Learning (ICL) enables off-the-shelf

arXiv:2604.19750v1 Announce Type: cross Abstract: Recent advances in Large Language Model (LLM)-based agents have shown remarkable progress in code generation. However, current agent methods mainly re

arXiv:2604.20027v1 Announce Type: cross Abstract: For state-of-the-art image understanding, Vision Transformers (ViTs) have become the standard architecture but their processing diverges substantially

arXiv:2604.20021v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become increasingly popular, caching responses so that they can be reused by users with semantically similar queries h

arXiv:2604.20098v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently hallucinate, limiting their reliability in critical applications. Conformal Prediction (CP) addresses this by ca

arXiv:2601.14295v3 Announce Type: replace Abstract: Large language models increasingly function as artificial reasoners: they evaluate arguments, assign credibility, and express confidence. Yet their

arXiv:2604.20133v1 Announce Type: new Abstract: This paper proposes EvoAgent - an evolvable large language model (LLM) agent framework that integrates structured skill learning with a hierarchical sub

arXiv:2604.19761v1 Announce Type: new Abstract: Modern machine learning is still largely organized around a single recipe: choose a parameterized model family and optimize its weights. Although highly

LlamaIndex have a most excellent open source project called LiteParse, which provides a Node.js CLI tool for extracting text from PDFs. I got a version of LiteParse working entirely in the browser, us

This Reddit discussion post addresses a beginner's question about choosing between 3B and 7B parameter models for fine-tuning on multi-task reasoning problems. The post likely contains advice from exp

arXiv:2603.09046v2 Announce Type: replace-cross Abstract: Device-side Large Language Models (LLMs) have witnessed explosive growth, offering higher privacy and availability compared to cloud-side LLMs

Rumors suggest OpenAI may release GPT-5.5 on April 23, 2026 , following accidental leaks of the model in OpenAI's Codex platform that showed GPT-5.5 alongside other unreleased models . Internally code

The Verge: GPT-5.5 is rolling out to Plus, Pro, Business, and Enterprise users in ChatGPT and Codex, and GPT-5.5 Pro to Pro, Business, and Enterprise users in ChatGPT — The new model ‘excels’ at tasks

GPT-5.5 achieved state-of-the-art performance on the ARC-AGI-2 benchmark, with scores ranging from 85.0% on maximum difficulty tasks to 33% on low difficulty tasks. The model demonstrated consistent i

arXiv:2604.19783v1 Announce Type: new Abstract: Which persuasion strategies, if any, are associated with donation compliance? Answering this requires fine-grained strategy labels across a full corpus

arXiv:2604.20157v1 Announce Type: new Abstract: Recent advances in model architectures, compute, and data scale have driven rapid progress in video generation, producing increasingly realistic content

arXiv:2604.20244v1 Announce Type: cross Abstract: Knowledge distillation (KD) is a powerful paradigm for compressing large language models (LLMs), whose effectiveness depends on intertwined choices of

arXiv:2503.08321v2 Announce Type: replace Abstract: Vision graph neural networks have emerged as a popular approach for modeling the global and spatial context for image recognition. However, a signif

important (and very jakub-coded) jakub quote: OpenAI Unveils GPT-5.5. Company Says Expect a Faster Model Release Pace 👀 OpenAI: 'We see pretty significant improvements in the short term, extremely sig

I've been previewing this in Codex for a few weeks - it's very good! Had some great results from it having it run security reviews against code written using other models Introducing GPT-5.5 A new cla

arXiv:2604.20545v1 Announce Type: new Abstract: In measurement theory, instruments do not simply record reality; they help constitute what is observed. The same holds for generative AI evaluation: ben

arXiv:2604.19902v1 Announce Type: cross Abstract: We present MMCORE, a unified framework designed for multimodal image generation and editing. MMCORE leverages a pre-trained Vision-Language Model (VLM

arXiv:2604.20719v1 Announce Type: cross Abstract: Omnimodal Notation Processing (ONP) represents a unique frontier for omnimodal AI due to the rigorous, multi-dimensional alignment required across aud

arXiv:2604.19823v1 Announce Type: cross Abstract: Rabies remains a major public health concern across many African and Asian countries, where accurate diagnosis is critical for effective epidemiologic

arXiv:2604.20738v1 Announce Type: new Abstract: We introduce a benchmark dataset for question answering and translation in bilingual Latin and English settings, containing about 7,800 question-answer