Search: “model-releases”

arXiv:2609.10060v1 Announce Type: new Abstract: Existing bias auditing methods typically rely on model outputs, requiring costly benchmarks or judge models and potentially missing internal shifts that

arXiv:2411.06429v2 Announce Type: replace Abstract: Quantum Tiq-Taq-Toe is a well-known benchmark and playground for both quantum computing and machine learning. Despite its popularity, no reinforceme

arXiv:2603.23346v2 Announce Type: replace Abstract: Real-time spoken dialogue systems face a fundamental tension between latency and response quality. End-to-end speech-to-speech (S2S) models respond

arXiv:2609.09409v1 Announce Type: cross Abstract: Near-field localization is a promising technique for high-resolution multi-user positioning in future wireless systems, but its performance is often d

Remember kids, if you take out loans to get a college degree, you assume the risk that you might not be able to pay them back but if you're a farmer getting hosed by Trump's idiotic policies, there's

arXiv:2609.09657v1 Announce Type: new Abstract: Existing emotional support conversation systems mainly focus on one-on-one seeker-supporter interactions and individual emotional states, leaving interp

arXiv:2609.11864v1 Announce Type: cross Abstract: Speech large language models (SpeechLLMs) offer reduced latency and retain paralinguistic nuances that are typically lost in cascaded automatic speech

arXiv:2609.10798v1 Announce Type: cross Abstract: Image-metadata prediction requires fusing heterogeneous evidence whose reliability can vary across samples and latent factors. Existing representation

arXiv:2609.10950v1 Announce Type: new Abstract: Recent multimodal sentiment analysis studies increasingly adopt text-centric fusion approaches to exploit the rich sentiment information inherent in the

I can't stand kv cache quantization. Even at q8_0, I can feel the difference. But realistically, when running Qwen3.8-27B-UD-Q4_K_XL on my 32 GB GPU, I only have room for ~170k tokens (with mtp and mm

arXiv:2609.09678v1 Announce Type: new Abstract: Clinical diagnosis agents must decide not only what test to request next, but also when to diagnose or defer. Existing agent benchmarks largely evaluate

Sakana AI 社の最新 AI「Fugu Max」に、NVIDIA のオープンモデル「Nemotron」ファミリーが組み込まれています🐡✨オープンモデルの連携がもたらす革新的なパフォーマンス、ぜひ引用元のブログでチェックしてみてください👇 Introducing Fugu Max and Fugu Ultra v2: the next evolution of Sakana Fugu’s mu

arXiv:2609.11144v1 Announce Type: cross Abstract: Financial NLP has a standard workflow: validate a sentiment tool against human labels, then trust it to extract market signal. This assumes the two ev

arXiv:2609.11355v1 Announce Type: new Abstract: This paper describes our system for Task~2 of the second Multilingual Conversational Speech Language Model (MLC-SLM) Challenge. We adapt Qwen3-Omni-30B-

arXiv:2412.16078v2 Announce Type: replace Abstract: Improving the reliability and completeness of colonoscopic inspection is critical for reducing missed lesions and improving colorectal cancer preven

arXiv:2609.11650v1 Announce Type: new Abstract: Accurate identification of end-diastole (ED) and end-systole (ES) in echocardiography underpins the quantification of ventricular function, yet manual s

arXiv:2607.18116v2 Announce Type: replace-cross Abstract: Recent work leverages Large Language Models (LLMs) to generate executable code for pedagogical animations using libraries such as Manim. Howev

arXiv:2609.10787v1 Announce Type: new Abstract: Accurate modelling of illumination is central to realistic image synthesis and scene understanding. Yet, there is little exploration into whether image

arXiv:2601.19285v3 Announce Type: replace Abstract: Diffusion models achieve remarkable generation quality, yet face a fundamental challenge known as memorization, where generated samples can replicat

arXiv:2609.10627v1 Announce Type: cross Abstract: Machine learning explanations reveal model behavior beyond predictions, creating attack surfaces for model confidentiality and data privacy. We system

arXiv:2609.11228v1 Announce Type: new Abstract: Applying knowledge transfer across multiple optimization tasks, multitask optimization (MTO) emerges as a promising approach to solving synergistic opti

arXiv:2604.00280v2 Announce Type: replace-cross Abstract: Formal specifications play a central role in ensuring software reliability, yet automatically synthesizing high-quality specifications remains

arXiv:2609.11703v1 Announce Type: new Abstract: Accurate segmentation of colorectal liver metastases (CRLM) in contrast-enhanced computed tomography (CT) is important for response assessment, surgical

I’ve been building 'Spomin', a router that replaces context with summaries directly in the KV cache. The goal is to keep long running sessions going without repeatedly stopping for full compaction and

arXiv:2609.10883v1 Announce Type: cross Abstract: Language models are trained to implement a helpful AI Assistant character (e.g., Claude). We explore how finetuning on synthetic stories affects this

arXiv:2609.11505v1 Announce Type: new Abstract: Efficient language learning requires methods to reduce the reliance on large data and computational resources. We investigate structural transfer: First

arXiv:2609.10923v1 Announce Type: new Abstract: Graph captions should help readers understand graph structure, rather than simply translate adjacency matrices into long textual edge lists. A useful gr

arXiv:2609.11687v1 Announce Type: new Abstract: We revisit Kashin-decomposition-based weight quantization for large language models and propose an improved algorithm with stronger convergence properti

arXiv:2609.10824v1 Announce Type: cross Abstract: Before an LLM agent tackles tasks in a new environment, it can inspect available corpora and tools and construct reusable resources such as indices, s

arXiv:2609.09848v1 Announce Type: cross Abstract: Synthetic data releases are increasingly proposed in the literature as a means of sharing realistic data replicas in lieu of sensitive private dataset

arXiv:2609.10898v1 Announce Type: new Abstract: Crystal-orientation maps are physical fields defined only up to crystal symmetry; electron backscatter diffraction (EBSD) resolves them experimentally,

arXiv:2609.10742v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) are powerful models for handling attributed graphs in tasks such as classification, link prediction, and community detect

arXiv:2609.11042v1 Announce Type: new Abstract: Agent usage is shifting toward long-horizon tasks such as coding and scientific discovery, among which terminal tasks are especially important. We intro

Some people says terminal bench reflects model intelligence better than the intelligent index. From the look of it, the ranking does seem to reflect how people feel about the open and closed models. F

That's amazing. I've been using the pay-as-you-go plan, and because DeepSeek 4 Flash wasn't great, I was using GLM 5.3 Flash instead. But now that I'm using the high-performing DeepSeek 4.1 Flash, the

arXiv:2609.09853v1 Announce Type: new Abstract: LLM agents for enterprise systems of record cannot be evaluated on customer production data, and no existing substitute provides ground truth. We presen

arXiv:2609.10947v1 Announce Type: cross Abstract: We propose the Platonic brain bridge hypothesis: omni models, which process video, audio and text jointly like the brain, converge on brain-like repre

arXiv:2609.10739v1 Announce Type: cross Abstract: A truth probe fitted where truthful reporting and a task's prescribed action coincide cannot distinguish those targets from its fitting labels alone.

arXiv:2609.10745v1 Announce Type: new Abstract: Multimodal entity linking grounds entity mentions in text and images to knowledge-base entries. These systems degrade on rare entities, but prior work m

Bloomberg: Threat intelligence report: Anthropic says it disrupted a Yemen-based guided weapons engineering cell using Claude to develop guidance software for missiles — Anthropic PBC uncovered a grou

arXiv:2601.15645v2 Announce Type: replace Abstract: Large-scale language models (LLMs) often offer clinical judgments based on incomplete information, increasing the risk of misdiagnosis. Existing stu

arXiv:2609.11399v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for machine translation, yet their outputs often contain additional text beyond the translation itsel

arXiv:2609.03247v1 Announce Type: cross Abstract: Large language model (LLM) security has largely focused on role-playing jailbreaks, with less attention to what happens when a user asks an LLM to ver

arXiv:2609.10789v1 Announce Type: new Abstract: Diffeomorphic image registration is central to medical image analysis, enabling anatomically consistent alignment across subjects. Most learning-based d

arXiv:2609.11156v1 Announce Type: new Abstract: All-in-One medical image restoration (MedIR) aims to address diverse tasks across modalities and degradation types using a single universal model. Exist

LM Studio is a US‑hosted platform that enables “Zero Data Retention” by default, meaning user inputs are not stored after processing. It currently hosts the DeepSeek V4.1 Flash model—a 552 B multimoda