Search: “models”

arXiv:2511.19204v3 Announce Type: replace Abstract: We present a sampling-based model predictive control (MPC) framework that enables emergent locomotion without relying on handcrafted gait patterns o

hardwarearxiv-cs-ro

Schema Key Wording as an Instruction Channel in Structured Generation under Constrained Decoding

DGX agent

arXiv:2604.14862v1 Announce Type: new Abstract: Constrained decoding has been widely adopted for structured generation with large language models (LLMs), ensuring that outputs satisfy predefined forma

model-releasesarxiv-cs-cl

17 Apr 2026

The king reigns supreme This is likely going to be the best finetune of qwen 3.6 35b https://huggingface.co/DJLougen/Ornstein3.6-35B-A3B-GGU…

model-releasesclem-delangue--x

This post announces Ornstein3.6-35B-A3B-GGU, a fine-tuned variant of Qwen 3.6 35B model available on Hugging Face, with the author claiming it represents a high-quality optimization of the base model.

Applications

Variance Computation for Weighted Model Counting with Knowledge Compilation Approach

arXiv:2601.03523v2 Announce Type: replace Abstract: One of the most important queries in knowledge compilation is weighted model counting (WMC), which has been applied to probabilistic inference on va

applicationsarxiv-cs-ai

When Does Content-Based Routing Work? Representation Requirements for Selective Attention in Hybrid Sequence Models

arXiv:2603.20997v2 Announce Type: replace Abstract: We identify a routing paradox in hybrid sequence models: content-based routing - deciding which tokens deserve expensive attention - requires pairwi

researcharxiv-cs-lg

A ghost mechanism: An analytical model of abrupt learning in recurrent networks

arXiv:2501.02378v2 Announce Type: replace Abstract: Abrupt learning is a common phenomenon in recurrent neural networks (RNNs) trained on working memory tasks. In such cases, the networks develop tran

Adaptive Conformal Prediction for Improving Factuality of Generations by Large Language Models

arXiv:2604.13991v1 Announce Type: new Abstract: Large language models (LLMs) are prone to generating factually incorrect outputs. Recent work has applied conformal prediction to provide uncertainty es

An Empirical Investigation of Practical LLM-as-a-Judge Improvement Techniques on RewardBench 2

arXiv:2604.13717v1 Announce Type: new Abstract: LLM-as-a-judge, using a language model to score or rank candidate responses, is widely used as a scalable alternative to human evaluation in RLHF pipeli

Chain of Uncertain Rewards with Large Language Models for Reinforcement Learning

arXiv:2604.13504v1 Announce Type: cross Abstract: Designing effective reward functions is a cornerstone of reinforcement learning (RL), yet it remains a challenging and labor-intensive process due to

Echoes Over Time: Unlocking Length Generalization in Video-to-Audio Generation Models

arXiv:2602.20981v3 Announce Type: replace Abstract: Scaling multimodal alignment between video and audio is challenging, particularly due to limited data and the mismatch between text descriptions and

safetyarxiv-cs-cv

Evaluating the Formal Reasoning Capabilities of Large Language Models through Chomsky Hierarchy

arXiv:2604.02709v2 Announce Type: replace Abstract: The formal reasoning capabilities of LLMs are crucial for advancing automated software engineering. However, existing benchmarks for LLMs lack syste

Flow-based Generative Modeling of Potential Outcomes and Counterfactuals

arXiv:2505.16051v4 Announce Type: replace-cross Abstract: Predicting potential and counterfactual outcomes from observational data is central to individualized decision-making, particularly in clinica

Agents

GPT-Rosalind, our Life Sciences model series, is optimized for scientific workflows, with stronger performance in protein and chemical reaso…

GPT-Rosalind, our Life Sciences model series, is optimized for scientific workflows, with stronger performance in protein and chemical reasoning, genomics analysis, biochemistry knowledge, and scienti

agentsopenai--x

Stein Variational Uncertainty-Adaptive Model Predictive Control

model-releasesarxiv-cs-ro

arXiv:2604.01034v2 Announce Type: replace Abstract: We propose a Stein variational distributionally robust controller for nonlinear dynamical systems with latent parametric uncertainty. The method is

Text-Attributed Knowledge Graph Enrichment with Large Language Models for Medical Concept Representation

arXiv:2604.13331v1 Announce Type: new Abstract: In electronic health record (EHR) mining, learning high-quality representations of medical concepts (e.g., standardized diagnosis, medication, and proce

Local Ai

Which video model currently has the best face likeness for LoRA training?

local-air-stablediffusion

This r/StableDiffusion thread discusses community comparisons of video generation models (such as those built on Stable Diffusion or FLUX architectures) evaluated specifically for how well they preser

Agents

AutoSurrogate: An LLM-Driven Multi-Agent Framework for Autonomous Construction of Deep Learning Surrogate Models in Subsurface Flow

arXiv:2604.11945v1 Announce Type: cross Abstract: High-fidelity numerical simulation of subsurface flow is computationally intensive, especially for many-query tasks such as uncertainty quantification

agentsarxiv-cs-ai

[b]=[d]-[t]+[p]: Self-supervised Speech Models Discover Phonological Vector Arithmetic

arXiv:2602.18899v3 Announce Type: replace-cross Abstract: Self-supervised speech models (S3Ms) are known to encode rich phonetic information, yet how this information is structured remains underexplor

Challenging Vision-Language Models with Physically Deployable Multimodal Semantic Lighting Attacks

arXiv:2604.12833v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown remarkable performance, yet their security remains insufficiently understood. Existing adversarial studies focu

safetyarxiv-cs-cv

Tutorials

Characterizing higher-order representations through generative diffusion models explains human decoded neurofeedback performance

arXiv:2503.14333v4 Announce Type: replace-cross Abstract: Brains construct not only 'first-order' representations of the environment but also 'higher-order' representations about those representations

tutorialsarxiv-cs-ai

Claude Opus 4.7 on Vertex AI

model-releasesgoogle-cloud-ai

Today, we’re announcing the general availability of Claude Opus 4.7 on Vertex AI. What’s new: Anthropic’s newest Opus model delivers advanced performance across coding, long-running agents, and profes

Local Ai

ERNIE-Image is now in ComfyUI An open-source 8B DiT text-to-image model from @ErnieforDevs, licensed under Apache-2.0. Key highlights: - Ope…

ERNIE-Image is now in ComfyUI An open-source 8B DiT text-to-image model from @ErnieforDevs, licensed under Apache-2.0. Key highlights: - Open-source under Apache-2.0 license - Precise multilingual tex

local-aicomfyui--x

Applications

Evaluating Robustness of Large Language Models Against Multilingual Typographical Errors

arXiv:2510.09536v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in multilingual, real-world applications with user inputs -- naturally introducing typographi

applicationsarxiv-cs-cl

Growing Pains: Extensible and Efficient LLM Benchmarking Via Fixed Parameter Calibration

arXiv:2604.12843v1 Announce Type: new Abstract: The rapid release of both language models and benchmarks makes it increasingly costly to evaluate every model on every dataset. In practice, models are

Human-Centric Topic Modeling with Goal-Prompted Contrastive Learning and Optimal Transport

arXiv:2604.12663v1 Announce Type: new Abstract: Existing topic modeling methods, from LDA to recent neural and LLM-based approaches, which focus mainly on statistical coherence, often produce redundan

I spent some time trying to distill all the complex factors impacting open models -- economics, capabilities, distribution, policy, etc. -- …

I spent some time trying to distill all the complex factors impacting open models -- economics, capabilities, distribution, policy, etc. -- into a clear list of beliefs. Here they are in full. 1. It’s

safetyyann-lecun--x

KG-Reasoner: A Reinforced Model for End-to-End Multi-Hop Knowledge Graph Reasoning

arXiv:2604.12487v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit strong abilities in natural language understanding and generation, yet they struggle with knowledge-intensive rea

researcharxiv-cs-ai

Applications

Knowledge Is Not Static: Order-Aware Hypergraph RAG for Language Models

arXiv:2604.12185v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enhances large language models by grounding outputs in retrieved knowledge. However, existing RAG methods including

applicationsarxiv-cs-cl

Latent-Condensed Transformer for Efficient Long Context Modeling

arXiv:2604.12452v1 Announce Type: new Abstract: Large language models (LLMs) face significant challenges in processing long contexts due to the linear growth of the key-value (KV) cache and quadratic

Models Know Their Shortcuts: Deployment-Time Shortcut Mitigation

arXiv:2604.12277v1 Announce Type: new Abstract: Pretrained language models often rely on superficial features that appear predictive during training yet fail to generalize at test time, a phenomenon k

safetyarxiv-cs-lg

Industry

More people should work on harnesses for open and local models!

Hugging Face co-founder and CEO Clément Delangue advocates for more developers and researchers to focus on building evaluation harnesses and testing frameworks specifically designed for open-source an

industryclem-delangue--x

Parcae: Scaling Laws For Stable Looped Language Models

arXiv:2604.12946v1 Announce Type: new Abstract: Traditional fixed-depth architectures scale quality by increasing training FLOPs, typically through increased parameterization, at the expense of a high

Point Prompting: Counterfactual Tracking with Video Diffusion Models

arXiv:2510.11715v2 Announce Type: replace Abstract: Trackers and video generators solve closely related problems: the former analyze motion, while the latter synthesize it. We show that this connectio

researcharxiv-cs-cv

ReasonXL: Shifting LLM Reasoning Language Without Sacrificing Performance

arXiv:2604.12378v1 Announce Type: new Abstract: Despite advances in multilingual capabilities, most large language models (LLMs) remain English-centric in their training and, crucially, in their produ

ResBM: Residual Bottleneck Models for Low-Bandwidth Pipeline Parallelism

arXiv:2604.11947v1 Announce Type: cross Abstract: Unlocking large-scale low-bandwidth decentralized training has the potential to utilize otherwise untapped compute resources. In centralized settings,

researcharxiv-cs-ai

Tutorials

Siamese Foundation Models for Crystal Structure Prediction

arXiv:2503.10471v2 Announce Type: replace-cross Abstract: Predicting crystal structures from chemical compositions is a fundamental challenge in materials discovery, complicated by complex 3D geometri

tutorialsarxiv-cs-ai

SparseWorld-TC: Trajectory-Conditioned Sparse Occupancy World Model

model-releasesarxiv-cs-cv

arXiv:2511.22039v3 Announce Type: replace Abstract: This paper introduces a novel architecture for trajectory-conditioned forecasting of future 3D scene occupancy. In contrast to methods that rely on

The A-R Behavioral Space: Execution-Level Profiling of Tool-Using Language Model Agents in Organizational Deployment

arXiv:2604.12116v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as tool-augmented agents capable of executing system-level operations. While existing benchmarks

VULCAN: Vision-Language-Model Enhanced Multi-Agent Cooperative Navigation for Indoor Fire-Disaster Response

model-releasesarxiv-cs-ro

arXiv:2604.12831v1 Announce Type: new Abstract: Indoor fire disasters pose severe challenges to autonomous search and rescue due to dense smoke, high temperatures, and dynamically evolving indoor envi

WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering

arXiv:2604.05818v2 Announce Type: replace-cross Abstract: Multi-modal Retrieval-Augmented Generation (RAG) has emerged as a highly effective paradigm for Knowledge-Based Visual Question Answering (KB-

Tutorials

A robust and adaptive MPC formulation for Gaussian process models

arXiv:2507.02098v2 Announce Type: replace-cross Abstract: In this paper, we present a robust and adaptive model predictive control (MPC) framework for uncertain nonlinear systems affected by bounded d

tutorialsarxiv-cs-lg

ASPIRin: Action Space Projection for Interactivity-Optimized Reinforcement Learning in Full-Duplex Speech Language Models

arXiv:2604.10065v1 Announce Type: cross Abstract: End-to-end full-duplex Speech Language Models (SLMs) require precise turn-taking for natural interaction. However, optimizing temporal dynamics via st

BoxTuning: Directly Injecting the Object Box for Multimodal Model Fine-Tuning

arXiv:2604.11136v1 Announce Type: cross Abstract: Object-level spatial-temporal understanding is essential for video question answering, yet existing multimodal large language models (MLLMs) encode fr

researcharxiv-cs-ai

ChemPro: A Progressive Chemistry Benchmark for Large Language Models

arXiv:2602.03108v3 Announce Type: replace Abstract: We introduce ChemPro, a progressive benchmark with 4100 natural language question-answer pairs in Chemistry, across 4 coherent sections of difficult

CLSGen: A Dual-Head Fine-Tuning Framework for Joint Probabilistic Classification and Verbalized Explanation

arXiv:2604.11801v1 Announce Type: new Abstract: With the recent progress of Large Language Models (LLMs), there is a growing interest in applying these models to solve complex and challenging problems

CoSToM:Causal-oriented Steering for Intrinsic Theory-of-Mind Alignment in Large Language Models

arXiv:2604.10031v1 Announce Type: cross Abstract: Theory of Mind (ToM), the ability to attribute mental states to others, is a hallmark of social intelligence. While large language models (LLMs) demon

DeCoVec: Building Decoding Space based Task Vector for Large Language Models via In-Context Learning

arXiv:2604.11129v1 Announce Type: new Abstract: Task vectors, representing directions in model or activation spaces that encode task-specific behaviors, have emerged as a promising tool for steering l

dTRPO: Trajectory Reduction in Policy Optimization of Diffusion Large Language Models

arXiv:2603.18806v2 Announce Type: replace Abstract: Diffusion Large Language Models (dLLMs) introduce a new paradigm for language generation, which in turn presents new challenges for aligning them wi