Search: “models”

arXiv:2604.23108v1 Announce Type: cross Abstract: Large Language Models (LLMs) based on Mixture-of-Experts (MoE) are pivotal in industrial applications for their ability to scale performance efficient

arXiv:2506.01897v5 Announce Type: replace Abstract: With increasing size of large language models (LLMs), full-parameter fine-tuning imposes substantial memory demands. To alleviate this, we propose a

arXiv:2604.24472v1 Announce Type: cross Abstract: Multi-behavior recommendation aims to predict user conversions by modeling various interaction types that carry distinct intent signals. Recently, gen

arXiv:2603.14228v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has become a cornerstone of parameter-efficient fine-tuning (PEFT). Yet, its efficacy is hampered by two fundamental limi

Today, we are excited to announce the day zero availability of NVIDIA Nemotron 3 Nano Omni on Amazon SageMaker JumpStart. In this post, we walk through the model architecture and key capabilities of N

Pi + local models are definitely really cool! Short demo to clean up my Desktop: > terminal 1: llama-server -hf unsloth/Qwen3.5-9B-GGUF:UD-Q4_K_XL > terminal 2: simply type 'pi' and start talking to i

arXiv:2604.24126v1 Announce Type: new Abstract: Automatic depression detection from conversational interactions holds significant promise for scalable screening but remains hindered by severe data sca

arXiv:2604.23972v1 Announce Type: cross Abstract: Knowledge graphs (KGs) are increasingly used to support large lan guage model (LLM) reasoning, but standard triplet-based KGs treat each relation as g

arXiv:2604.24198v1 Announce Type: cross Abstract: Process Reward Models (PRMs) have achieved remarkable success in augmenting the reasoning capabilities of Large Language Models (LLMs) within static d

arXiv:2512.23213v3 Announce Type: replace-cross Abstract: We propose LLM-PeerReview, an unsupervised LLM Ensemble method that selects the most ideal response from multiple LLM-generated candidates for

arXiv:2508.19652v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) often suffer from visual hallucinations: generating things that are not consistent with visual inputs and language sho

arXiv:2601.15485v2 Announce Type: replace-cross Abstract: Federal research funding shapes the direction, diversity, and impact of the US scientific enterprise. Large language models (LLMs) are rapidly

arXiv:2512.10362v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) demonstrate impressive reasoning capabilities, but often fail to perceive fine-grained visual details

Want to see which frontier models do the best on document understanding? Check out our ParseBench leaderboard on @kaggle! https://www.kaggle.com/benchmarks/llamaindex-org/parsebench For more details o

arXiv:2604.21952v1 Announce Type: cross Abstract: This work presents a multi-layered methodology for efficiently accelerating multimodal foundation models (MFMs). It combines hardware and software co-

arXiv:2604.22193v1 Announce Type: new Abstract: Large language models (LLMs) often need to balance their internal parametric knowledge with external information, such as user beliefs and content from

arXiv:2604.22631v1 Announce Type: new Abstract: Modern automatic speech recognition (ASR) systems have been observed to function better for certain speaker groups (SGs) than others, despite recent gai

arXiv:2604.22411v1 Announce Type: new Abstract: Even when decoding with temperature T=0, large language models (LLMs) can produce divergent outputs for identical inputs. Recent work by Thinking Machin

New work with @AlecRad and @DavidDuvenaud: Have you ever dreamed of talking to someone from the past? Introducing talkie, a 13B model trained only on pre-1931 text. Vintage models should help us to un

arXiv:2604.22136v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly issue API calls that mutate real systems, yet many current architectures pass stochastic model outputs

arXiv:2601.12430v2 Announce Type: replace Abstract: Vision-language model (VLM) hallucination is commonly linked to imbalanced allocation of attention across input modalities: system, image and text.

I don’t think there will be any coding models 3-4 years from now. completely disagree. buying Cursor is a genius move by Elon. wouldn't be surprised if xAI had the best coding model 12-18 months from

In other words, you need the world models that LeCun, Schmidhuber, Fei Fei Li, and I have been advocating for all along. Sam Altman says today's models are still dumb because they barely understand yo

A quantized version of DeepSeek-V4-Flash has been released on Hugging Face by the MLX community in 2-bit format with dynamic quantization, making the model more efficient for inference on resource-con

The community can now download pre-quantized weights from MLX community repo on HF thanks to @LambdaAPI Model collection: https://huggingface.co/collections/mlx-community/deepseek-v4 DeepSeek-V4-Flash

DeepSeek released V4 Pro (1.6T-A49B) and Flash (284B-A13B) models in both base and instruct variants, with optimizations enabling them to run on Huawei Ascend chips. These releases represent updates t

grok imagine is on another level now. the new model is unreal. go try it. Grok Imagine now has dramatically improved lip sync and sharper audio quality on all image-to-video generations. Dialogue trac

Local models do seem likely to create an explosion of new use cases. Local compute >> cloud compute. This is where we are right now. And i’m not gonna lie it feels pretty magical 🧚‍♀️ Qwen3.6 27B runn

arXiv:2604.20994v1 Announce Type: cross Abstract: The growth of agentic AI has drawn significant attention to function calling Large Language Models (LLMs), which are designed to extend the capabiliti

arXiv:2510.15313v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly applied to creative domains, yet their performance in classical Chinese poetry generation and evaluati

arXiv:2601.05019v2 Announce Type: replace-cross Abstract: Recent Large Reasoning Models trained via reinforcement learning exhibit a 'natural' alignment with human cognitive costs. However, we show th

Reuters: Huawei says its Ascend supernode based on the Ascend 950 AI chips will fully support DeepSeek V4, as DeepSeek launches a preview of its V4 model — Huawei Technologies said on Friday its Ascen

I had a range of models 'build me a procedurally generated 3D simulation showing the evolution of a harbor town from 3000 BCE to 3000 AD' in one prompt. You can play the full gallery here: https://hg-

Introducing DeepSeek V4 Pro, a long-context model with hybrid attention, three reasoning modes, and SOTA coding performance. AI natives can now use DeepSeek V4 Pro on Together AI and benefit from reli

arXiv:2604.21061v1 Announce Type: new Abstract: The application of artificial intelligence (AI) in IVF has shown promise in improving consistency and standardization of decisions, but often relies on

The Klein 9B Distilled is a distilled image generation model enabling sub-second image generation with text-to-image and image-to-image editing capabilities in a single unified model, designed for rea

Listening to startups like @InstalilyAI, @UnslothAI, @splinetool, @ollama, and more talk about how they're using Gemini and Gemma models in production. 🙌🚀 Can't wait for the @garrytan @demishassabis f

arXiv:2511.20697v4 Announce Type: replace-cross Abstract: Understanding complete musical scores entails integrated reasoning over pitch, rhythm, harmony, and large-scale structure, yet the ability of

arXiv:2604.21036v1 Announce Type: new Abstract: Text-to-image(T2I) models like Stable Diffusion and DALL-E have made generative AI widely accessible, yet recent studies reveal that these systems often

IBM Research has developed an AI model designed to analyze and predict the behavior of fusion plasma, advancing computational capabilities for nuclear fusion research. The model likely leverages machi

arXiv:2510.08465v2 Announce Type: replace-cross Abstract: Estimating how individual input variables affect the output of a black-box model is a central task in explainable machine learning. However, e

arXiv:2604.20595v1 Announce Type: cross Abstract: We establish a mathematical correspondence between state space models, a state-of-the-art architecture for capturing long-range dependencies in data,

In this post, we'll explore how multimodal BioFMs work, showcase real-world applications in drug discovery and clinical development, and contextualize how AWS enables organizations to build and deploy

arXiv:2403.18151v2 Announce Type: replace-cross Abstract: Objective: Cytology plays a crucial role in lung cancer diagnosis. Pulmonary cytology involves cell morphological characterization in the spec

arXiv:2604.16902v2 Announce Type: replace Abstract: Native Omni-modal Large Language Models (OLLMs) have shifted from pipeline architectures to unified representation spaces. However, this native inte

By end of next year. End of year after for 16gb vram. Do folk really need more for most things? Not really. But just call the cloud models when you do. What's a reasonable timeline for a GPT 5.4/Opus