Search: “models”

arXiv:2604.06826v1 Announce Type: cross Abstract: Environmental, Social, and Governance (ESG) considerations are increasingly integral to assessing corporate performance, reputation, and long-term sus

applicationsarxiv-cs-ai

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Applications

HiF-VLA: Hindsight, Insight and Foresight through Motion Representation for Vision-Language-Action Models

DGX agent

arXiv:2512.09928v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have recently enabled robotic manipulation by grounding visual and linguistic cues into actions. However, most V

applicationsarxiv-cs-ro

10 Apr 2026

In-Context Learning in Speech Language Models: Analyzing the Role of Acoustic Features, Linguistic Structure, and Induction Heads

arXiv:2604.06356v1 Announce Type: cross Abstract: In-Context Learning (ICL) has been extensively studied in text-only Language Models, but remains largely unexplored in the speech domain. Here, we inv

PlaneCycle: Training-Free 2D-to-3D Lifting of Foundation Models Without Adapters

arXiv:2603.04165v3 Announce Type: replace-cross Abstract: Large-scale 2D foundation models exhibit strong transferable representations, yet extending them to 3D volumetric data typically requires retr

Plug-and-Play Logit Fusion for Heterogeneous Pathology Foundation Models

arXiv:2604.07779v1 Announce Type: new Abstract: Pathology foundation models (FMs) have become central to computational histopathology, offering strong transfer performance across a wide range of diagn

safetyarxiv-cs-cv

Prompt reinforcing for long-term planning of large language models

model-releasesarxiv-cs-cl

arXiv:2510.05921v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable success in a wide range of natural language processing tasks and can be adapted through prompt

Search-R3: Unifying Reasoning and Embedding in Large Language Models

arXiv:2510.07048v2 Announce Type: replace Abstract: Despite their remarkable natural language understanding capabilities, Large Language Models (LLMs) have been underutilized for retrieval tasks. We p

tutorialsarxiv-cs-cl

Some strong embeddings models have been released recently. Ours is still better. We benchmarked Embed 5 Fast against Google's EmbeddingGemma…

Some strong embeddings models have been released recently. Ours is still better. We benchmarked Embed 5 Fast against Google's EmbeddingGemma 2 across 163 datasets using RCP-nDCG@10. Embed 5 Fast leads

model-releasescohere--x

17 Oct 2026

Local Ai

Agent Skill Framework: Perspectives on the Potential of Small to Medium Language Models in Industrial Environments

arXiv:2602.16653v4 Announce Type: replace Abstract: Skills are getting increasingly used in recent agentic frameworks, performing robustly with proprietary LLMs. Yet, their effectiveness for small and

local-aiarxiv-cs-ai

Data Strategies for Large Language Models: A Unified Perspective on the Training Lifecycle

arXiv:2610.21681v1 Announce Type: new Abstract: Data strategy plays a central role in training large language models (LLMs). It governs the selection, weighting, and scheduling of training data, there

researcharxiv-cs-cl

Decision-FLIP: Budget-Free Structured Pruning for Gaussian Occupancy Models

model-releasesarxiv-cs-cv

arXiv:2610.20917v1 Announce Type: new Abstract: Occupancy predictors rely on large persistent banks of Gaussians or learned queries whose size is fixed by hand. Common pruning proxies, such as opacity

Hardware

Making every stage of medical device document assessment with large language models deterministic

arXiv:2610.21300v1 Announce Type: new Abstract: To show that a medical device complies with regulation, experts judge whether documents and records meet each requirement and record the judgment for ot

hardwarearxiv-cs-cl

N-Gram Memories at Two Bits: Quantizing Lookup Tables in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.21810v1 Announce Type: cross Abstract: Conditional memory expands language-model capacity through selective lookup, but the full embedding table must remain available for every possible inp

Noise-Space Reward Alignment for Few-Step Generative Models

arXiv:2610.21125v1 Announce Type: new Abstract: Few-step generative models produce high-quality samples in one or a few evaluations. However, steering them toward desired properties remains difficult,

On-Policy Residual Learning for Diffusion Language Models

arXiv:2610.20687v1 Announce Type: new Abstract: Residual context is key to unlocking the speed-quality Pareto frontier of diffusion language models (DLMs) by carrying forward predictive distributions

ReasonUni: Reasoning-Augmented Reconstruction Advances Unified Multimodal Models

arXiv:2610.20781v1 Announce Type: cross Abstract: Image-to-text (I2T) understanding and text-to-image (T2I) generation are dual tasks in unified multimodal models (UMMs). Reconstructive post-training

tutorialsarxiv-cs-ai

Benchmarking and Training Reward Models for Cross-Source Evidence Grounding in Search Agents

arXiv:2610.17827v1 Announce Type: new Abstract: Existing approaches to training and evaluating search agents focus heavily on final-answer quality, largely neglecting how generated answers map back to

Don't Run with Scissors: Pruning Breaks VLA Models but They Can Be Recovered

arXiv:2510.08464v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models are a promising paradigm for field robotics, but their deployment is bottlenecked by strict edge SWaP-C co

LoopArena: Benchmarking Models as Runtime Controllers for Loop Engineering

arXiv:2608.28281v2 Announce Type: replace Abstract: Loop Engineering is emerging as a practice for organizing development work around coding agents. Instead of writing each prompt by hand, practitione

PatientWM: Towards Generalizable Clinical World Models via Unified Patient States

arXiv:2610.17059v1 Announce Type: new Abstract: Clinical decisions depend on anticipating how a patient's condition will evolve as treatment is adjusted and new evidence becomes available. Existing me

ReaDy: Recurrent States as Dynamic Context for Speculative Drafting in Hybrid Linear Attention Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.20503v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by drafting multiple tokens per step, yet feature-based drafters rely on target hidden featur

Industry

Startup nFox to open-source its ‘sandbox’ for open AI models

Artificial intelligence governance startup nFOX Lab today launched a platform for managing owned large language models and announced plans to open-source Blockhouse, a security sandbox designed to res

industrysiliconangle

VLRLA: Deployment-Time Adaptation of Vision-Language-Action Models through In-Context Reinforcement Learning

arXiv:2610.19517v1 Announce Type: cross Abstract: Vision-language-action (VLA) models connect visual perception and language understanding with robot control, providing a foundation for instruction-co

safetyarxiv-cs-ro

We made inspecting models tensors on the Hugging Face Hub up to 20× faster ⚡ DeepSeek-V3.2: 9.2s → 0.45s GLM-5.3: 4.0s → 0.57s Qwen2.5-72B: …

model-releasesclem-delangue--x

In October 2026, Victor M announced a performance boost for inspecting model tensors on the Hugging Face Hub, achieving up to a 20× speed increase. Sample results include DeepSeek‑V3.2 dropping from 9

Weighted Ensemble Sampling for Rare-Event Estimation in Language Models

arXiv:2610.19202v1 Announce Type: new Abstract: Rare but severe failures of large language models can become practically significant at deployment scale. Estimating their probabilities with direct Mon

safetyarxiv-cs-cl

When a Conceptor Complement Becomes Gain: Operator Geometry and Behavioral Attribution in Language Models

arXiv:2610.16325v1 Announce Type: new Abstract: When a steering intervention changes a language model's behavior, which part of the intervention deserves the credit? We test this question for a target

A Sense of Proprioception in Language Models

arXiv:2610.17495v1 Announce Type: new Abstract: In humans, proprioception corresponds to the sense of self-movement or position, e.g. understanding the position of one's arm. This sense is often less

Beyond User-Side Defenses: Image Protection in Open-Weight Diffusion Models

arXiv:2610.16835v1 Announce Type: cross Abstract: Model providers can support image protection, but open-weight deployment introduces practical constraints. We propose four requirements: protection ef

safetyarxiv-cs-cv

Deploy and evaluate models with Amazon SageMaker JumpStart

Learn how to deploy an available model from Amazon SageMaker JumpStart, run a lightweight and repeatable performance test using the SageMaker Python SDK, and delete the endpoint when testing is comple

tutorialsaws-ml-blog

Diagnose-to-Generate: Eliminating Structural Distortions in Flow Models via Patch-Level Grounded Alignment

model-releasesarxiv-cs-cv

arXiv:2610.17882v1 Announce Type: new Abstract: Flow-based image generators achieve strong semantic synthesis but still produce localized structural distortions, such as malformed hands and limbs. Exi

Foundation Models for Event Prediction Across Heterogeneous Event Logs

model-releasesarxiv-cs-lg

arXiv:2610.17503v1 Announce Type: new Abstract: Event logs are ubiquitous across real-world domains, including business processes, manufacturing workflows, healthcare, and many other operational syste

FoveaTree: Information-Density Trees for Query-Guided Visual Token Pruning in Video Large Language Models

model-releasesarxiv-cs-cv

arXiv:2610.16744v1 Announce Type: new Abstract: Video large language models (Video LLMs) encode each frame into hundreds of visual tokens, making video inference expensive. Existing methods reduce thi

From Token Correction to Claim Admission: Training-Free Hallucination Mitigation for Large Vision-Language Models

arXiv:2610.17706v1 Announce Type: new Abstract: Large vision-language models often exhibit object hallucination, generating claims that are not supported by the input image. To mitigate this issue, we

researcharxiv-cs-cv

Local Ai

G^2WAM: World Action Models for Efficient and Geometry Grounded Image-Goal Navigation

arXiv:2610.16558v1 Announce Type: cross Abstract: World models capture environment dynamics and support counterfactual reasoning for planning. In image-goal navigation, where the target often lies bey

local-aiarxiv-cs-ro

Machine Learning-Based Prediction of Dengue Infection Using Clinical and Hematological Data from Bangladesh: A Comparative Analysis of Benchmark and Extended Prediction Models

model-releasesarxiv-cs-lg

arXiv:2610.14813v1 Announce Type: new Abstract: Dengue is a viral infection caused by the dengue virus (DENV) and a major public health concern in Bangladesh, where symptom overlap with other febrile

Revisiting Natural Language Prompts from Large Language Models for Open-Vocabulary Video Recognition

arXiv:2610.16666v1 Announce Type: new Abstract: Vision-language models (VLMs) like CLIP have shown great success in image tasks, however, applying CLIP to open-vocabulary video recognition poses chall

safetyarxiv-cs-cv

Understanding Helpfulness and Harmless Tension in Reward Models

arXiv:2606.13209v2 Announce Type: replace Abstract: Reward models (RMs) are a key component of reinforcement learning from human feedback, enabling the alignment of large language models with human va

Agents

Robots That Predict the Future: Dyna-2, Million-Hour World Models, & the Bitter Lesson of Robotics @DynaRobotics’s @JasonMa2020 explains how…

Robots That Predict the Future: Dyna-2, Million-Hour World Models, & the Bitter Lesson of Robotics @DynaRobotics’s @JasonMa2020 explains how world-action models predict the future to guide physical ro

agentsswyx--x

13 Oct 2026

Using Gemini 4 makes you realize how many other models must be distilling Claude/GPT (or using a similar training pipeline). It feels quite …

model-releasesethan-mollick--x

On October 13 2026, researcher Ethan Mollick tweeted that observing Gemini 4’s behavior reveals how many other LLMs are likely distilled from Claude or GPT—and thus use a similar training pipeline—mak

13 Oct 2026

Deploy decision models with llama.cpp on Amazon SageMaker AI

model-releasesaws-ml-blog

Learn how to deploy decision models with llama.cpp on Amazon SageMaker AI. This technical how-to serves OpenAI-compatible chat completions with the AWS Deep Learning Container for llama.cpp, then exte

Efficient Learning of Survival Analysis Models Under Outcome-Dependent Truncation and Censoring

arXiv:2610.12538v1 Announce Type: new Abstract: Modern machine learning models are typically trained on data assumed to be representative of the predictive tasks the model will face in the future, but

I tested GPT-5.6 and GPT-6 with Medium → Instant → Medium. Both models failed on Instant, both succeeded on Medium. Here's what I found.

I've been investigating some serious ChatGPT reliability issues over the past several days, and my latest tests revealed something particularly interesting: Both GPT-5.6 and GPT-6 showed problems unde

model-releasesr-chatgpt

Localized Generative Design of Ship Hulls with Diffusion Models and High-Fidelity Assessment

arXiv:2610.12870v1 Announce Type: cross Abstract: Practical ship design requires localized refinement and performance evaluation. This paper presents a reward-directed diffusion framework for localize

On the Design Space of Continuous Diffusion Language Models

arXiv:2610.13834v1 Announce Type: new Abstract: Continuous diffusion language models (CDLMs) promise to bring the benefits of continuous flow modelling to language, including accelerated sampling and

researcharxiv-cs-lg

Scalable Circuit Learning for Interpreting Large Language Models

arXiv:2606.16939v2 Announce Type: replace-cross Abstract: A prominent research direction in mechanistic interpretability is learning sparse circuits over LLM components to reveal how they jointly prod

Spa-Bench: A Real-Robot Benchmark for Spatial Grounding in Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2610.12696v1 Announce Type: new Abstract: Vision-language-action models (VLAs) offer a promising route toward general-purpose robotics by transferring semantic knowledge from large-scale vision-

TabReliBench: Evaluating Tabular Foundation Models Beyond Predictive Accuracy

model-releasesarxiv-cs-lg

arXiv:2610.13654v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are increasingly popular for their strong predictive performance. Many also provide posterior predictive distributions

Transformer-Based Masked Diffusion Models Provably Learn Distributions with Latent Structure

arXiv:2610.12544v1 Announce Type: new Abstract: Masked diffusion models (MDMs) generate discrete data by iteratively unmasking multiple tokens in parallel using a learned mask predictor. Their output

tutorialsarxiv-cs-lg