Search: “models”

RL2ML: Finite-Rollout Surrogate Objectives from Reinforcement Learning to Maximum Likelihood

arXiv:2605.30154v1 Announce Type: new Abstract: Correctness-based Reinforcement Learning with Verifiable Rewards (RLVR) trains language models from binary feedback on sampled outputs, but the objectiv

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Rooted Absorbed Prefix Trajectory Balance with Submodular Replay for GFlowNet Training

DGX agent

arXiv:2603.00454v2 Announce Type: replace-cross Abstract: Generative Flow Networks (GFlowNets) enable fine-tuning large language models to approximate reward-proportional posteriors, but they remain p

safetyarxiv-cs-ai

29 May 2026

Hardware

Run Step 3.7 Flash on NVIDIA GPUs with Enterprise-Ready Multimodal AI

Step 3.7 Flash is a 198B-parameter Mixture-of-Experts vision-language model designed for enterprise-scale production workloads, featuring native image and video input, a 256k context window, and confi

hardwarenvidia-developer

S2MDF: A Plug-And-Play Layer for Intersection-Free Multi-Object Signed Distance Fields

arXiv:2605.29761v1 Announce Type: new Abstract: Compositional implicit surface representations model scenes as collections of objects, each encoded by a Signed Distance Field (SDF). A fundamental limi

SafeRx-Agent: A Knowledge-Grounded Multi-Agent Framework for Safe and Explainable Medication Recommendation

arXiv:2605.29146v1 Announce Type: cross Abstract: Medication recommendation predicts medications for patient visits, but existing methods still face two key challenges. At the model level, traditional

SAVAA: Mitigating Hallucinations in LVLMs via Step-wise Adaptive Visual Attention Amplification

arXiv:2602.13600v2 Announce Type: replace Abstract: A line of recent training-free methods for mitigating hallucinations in large vision-language models (LVLMs) operates by amplifying attention to vis

SEAL: Can Saturated Benchmarks Be Revived by LLM-as-a-Meta-Judge?

arXiv:2605.30104v1 Announce Type: new Abstract: Widely used language-model benchmarks are increasingly saturated, with frontier systems often receiving near-tied scores that standard metrics cannot re

agentsarxiv-cs-cl

Solving Integer Linear Programming with Parallel Tempering

arXiv:2605.29366v1 Announce Type: new Abstract: Integer Linear Programming (ILP) serves as a versatile framework for modeling a wide range of combinatorial optimization problems, typically addressed b

researcharxiv-cs-lg

SuperVoxelGPT: Adaptive and Ordered 3D Tokenization for Autoregressive Shape Generation

arXiv:2605.29655v1 Announce Type: new Abstract: Autoregressive multimodal large language models (MLLMs) enable 3D generation but struggle to scale to high-resolution shapes due to inadequate 3D tokeni

Teaching Values to Machines: Simulating Human-Like Behavior in LLMs

arXiv:2605.30036v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate a remarkable capacity to adopt different personas and roles; however, it remains unclear whether they can manif

The Anatomy of Conversational Scams: A Topic-Based Red Teaming Analysis of Multi-Turn Interactions in LLMs

arXiv:2601.03134v2 Announce Type: replace Abstract: As LLMs gain persuasive capabilities through extended dialogues, they create new opportunities for studying adversarial conversational behavior in e

safetyarxiv-cs-cl

Towards Verifiable Multimodal Deep Research: A Multi-Agent Harness for Interleaved Report Generation

arXiv:2605.29861v1 Announce Type: cross Abstract: Large Language Models (LLMs) have advanced autonomous agents from deep search, which retrieves concise factual answers, to deep research, which synthe

Turbulence-Robust Dynamic Object Segmentation with Multi-Signal Priors and SAM2 Refinement

arXiv:2605.29292v1 Announce Type: new Abstract: This technical report presents our solution for the CVPR 2026 UG2+ Challenge Track 3: Dynamic Object Segmentation in Turbulence (DOST). We design a trai

UI-KOBE: Knowledge-Oriented Behavior Exploration for Lightweight Graph-Guided GUI Agents

arXiv:2605.29534v1 Announce Type: new Abstract: Recent advances in mobile GUI agents have shown strong potential for automating mobile tasks, but most effective systems still depend on large vision-la

local-aiarxiv-cs-ai

Understanding the Ability of LLMs to Handle Character-Level Perturbation

arXiv:2510.14365v4 Announce Type: replace Abstract: This work investigates the resilience of contemporary large language models (LLMs) against frequent character-level perturbations. We examine three

Tutorials

Uni-RCM: Unified Reference-guided Cross-modal Mapping for Multi-Class Anomaly Detection

arXiv:2605.29455v1 Announce Type: new Abstract: Multi-modal industrial anomaly detection typically relies on separate models for each product category, fundamentally limiting practical scalability. Wh

tutorialsarxiv-cs-cv

Unifying Temporal and Structural Credit Assignment in LLM-Based Multi-Agent Prompt Optimization

arXiv:2605.30227v1 Announce Type: cross Abstract: While Multi-Agent Systems (MAS) empower Large Language Models to tackle complex reasoning tasks through collaborative interaction, optimizing their dy

local-aiarxiv-cs-ai

User-Aware Active Knowledge Acquisition for Emotional Support Dialogue

arXiv:2605.29715v1 Announce Type: new Abstract: Emotional support plays an important role in dialogue systems, and its success depends on adapting to a user's evolving and implicit needs across multi-

safetyarxiv-cs-cl

V2XCrafter: Learning to Generate Driving Scene Across Agents

arXiv:2605.29471v1 Announce Type: new Abstract: Collaborative driving systems leverage vehicle-to-everything (V2X) communication for multi-agent collaborative perception to enhance driving safety, yet

safetyarxiv-cs-cv

Video fusion/join options

local-air-stablediffusion

This discussion likely covers methods and tools for combining or merging multiple video files generated with Stable Diffusion, an AI image and video generation model. Community members likely share re

VikingMem: A Memory Base Management System for Stateful LLM-based Applications

arXiv:2605.29640v1 Announce Type: new Abstract: Large Language Models have revolutionized interactive applications; however, their finite context windows pose a critical data management challenge for

[Web Chat para Ollama: Tu propia IA local, gratis y con privacidad total] [Local AI Web Chat for Ollama: 100% private, free, and runs entirely on your machine]

Web Chat para Ollama is a tool that enables users to run a private, free AI chat interface locally on their own machines using Ollama, an open-source framework for running large language models. The p

local-air-ollama

Hardware

What is the best used or refurbished laptop with GPU for open source Imege generation?

hardwarer-stablediffusion

This Reddit discussion in the StableDiffusion community addresses recommendations for affordable, used or refurbished laptops equipped with GPUs suitable for running open-source image generation model

Applications

When Does Persona Prompting Actually Help? A Retrieval and Metric Analysis of Expert Role Injection in LLMs

arXiv:2605.29420v1 Announce Type: new Abstract: Persona prompting is widely used to steer large language models, yet its practical value remains unclear. Prior work often evaluates persona prompting u

applicationsarxiv-cs-ai

WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction

arXiv:2605.29341v1 Announce Type: cross Abstract: Multimodal large language models are increasingly deployed as long-horizon agents, where memory must do more than recall: it must track an evolving wo

agentsarxiv-cs-cl

X-GS: An Extensible Framework for Perceiving and Thinking via 3D Gaussian Splatting

arXiv:2603.09632v3 Announce Type: replace-cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, subsequently extending into numerous spatial AI app

A New Era of Innovation: Google Research at I/O 2026

Google Research at I/O 2026 showcased new Gemini AI models including Gemini Omni, which can create content from any input starting with video, and Gemini 3.5 Flash, combining frontier intelligence wit

researchgoogle-research

Hardware

A Unified Structured Query Understanding Framework for Industrial Semantic Search

arXiv:2605.27441v1 Announce Type: cross Abstract: Query understanding in large-scale industrial search systems is typically implemented as a cascade of disparate, task-specific components. While indiv

hardwarearxiv-cs-lg

ABot-OCR Technical Report

arXiv:2605.27978v1 Announce Type: new Abstract: We introduce ABot-OCR, an end-to-end vision-language model that transcribes a page image directly into clean Markdown in a single forward pass. By doing

Agent Explorative Policy Optimization for Multimodal Agentic Reasoning

arXiv:2605.28774v1 Announce Type: new Abstract: Vision-language models with extended reasoning succeed on complex problems, but many real-world problems require external tools that internal reasoning

safetyarxiv-cs-cl

Tools

[AINews] Cognition raises 1B in 26B Series D

Cognition, an AI company, raised 1 billion in Series D funding at a 26 billion valuation, indicating significant investor confidence in its technology and business model. The funding round reflects th

toolslatent-space

Tutorials

Aligning LLMs with Human Uncertainty: A Beta-Bernoulli Calibrator for LLM Forecasting

arXiv:2605.27668v1 Announce Type: cross Abstract: Probabilistic forecasting estimates the likelihood of uncertain future events. To improve LLM forecasting, existing methods typically learn from binar

tutorialsarxiv-cs-ai

Are We Truly Innovating? A Qualitative and Quantitative Study of Originality in AI Research Papers

arXiv:2602.06054v3 Announce Type: replace Abstract: Assessing originality in AI research is arguably the most consequential yet least reliable step in peer review. Reviewer judgments of originality re

AtomComposer: Discovering Chemical Space from First Principles with Reinforcement Learning

arXiv:2605.28287v1 Announce Type: new Abstract: Discovering novel stable molecules without training data remains a grand scientific challenge. Current molecular generative models are trained on large,

agentsarxiv-cs-lg

Atomic Skills are the Prerequisite: When Reinforcement Learning Synthesizes Compositional Reasoning, and When It Only Amplifies

arXiv:2512.01970v3 Announce Type: replace Abstract: Does Reinforcement Learning (RL) merely amplify existing skills, or synthesize novel skills? We investigate this question through the lens of Comple

researcharxiv-cs-ai

BIRDNet: Mining and Encoding Boolean Implication Knowledge Graphs as Interpretable Deep Neural Networks

arXiv:2605.28739v1 Announce Type: cross Abstract: Tabular data in knowledge-rich domains often carries a latent prior in the form of Boolean implication relationships (BIRs) between pairs of features.

researcharxiv-cs-ai

BPPO: Binary Prefix Policy Optimization for Efficient GRPO-Style Reasoning RL with Concise Responses

arXiv:2605.28028v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) is widely used for training reasoning models, but updating all sampled completions in each group incurs substa

safetyarxiv-cs-lg

Challenges in Explaining Pretrained Clinical Text Classifiers

arXiv:2605.28060v1 Announce Type: new Abstract: Explaining the predictions of neural models in clinical NLP remains a significant challenge, especially for complex tasks involving long, unstructured m

Decoupling Skeleton and Flesh: Efficient Multimodal Table Reasoning with Disentangled Alignment and Structure-aware Guidance

arXiv:2602.03491v2 Announce Type: replace-cross Abstract: Reasoning over table images remains challenging for Large Vision-Language Models (LVLMs) due to complex layouts and tightly coupled structure-

local-aiarxiv-cs-cl

DeepC4: Deep Conditional Census-Constrained Clustering for Large-scale Multitask Spatial Disaggregation of Urban Morphology

arXiv:2507.22554v3 Announce Type: replace Abstract: To understand our global progress for sustainable development and disaster risk reduction in many developing economies, two recent major initiatives

local-aiarxiv-cs-lg

Defending LLM-based Multi-Agent Systems Against Cooperative Attacks with Sentence-Level Rectification

arXiv:2605.28104v1 Announce Type: new Abstract: Recent years have witnessed the rapid development of Large Language Model-based Multi-Agent Systems (MAS), which excel at collaborative decision-making

DeltaMCP: Incremental Regeneration via Spec-Aware Transformation for MCP servers

arXiv:2605.28148v1 Announce Type: cross Abstract: The rapid development of LLMs coupled with the introduction of Model Context Protocol (MCP) has revolutionized how intelligent agents interact with AP

Diagnosing Live Within-Policy Instruction Conflicts in LLM Agents with Witnessed Resolution Profiles

arXiv:2605.27784v1 Announce Type: new Abstract: LLM agents are governed by long-lived natural-language prompt policies, but individually reasonable standing rules can interact in uninspected ways. We

DIG to Heal: Scaling General-purpose Agent Collaboration via Explainable Dynamic Decision Paths

arXiv:2603.00309v2 Announce Type: replace Abstract: The increasingly popular agentic AI paradigm promises to harness the power of multiple, general-purpose large language model (LLM) agents to collabo

EAPO: Entropy-Driven Adaptive Positive-Negative Sample Weighting for Policy Optimization in Open-Ended QA

arXiv:2605.27846v1 Announce Type: new Abstract: Large Reasoning Models are typically trained via reinforcement learning from verifiable rewards (RLVR). However, existing approaches adopt fixed weights

EchoAvatar: Real-time Generative Avatar Animation from Audio Streams

arXiv:2605.28272v1 Announce Type: new Abstract: Real-time synthesis of high-fidelity 3D character motion from audio is a pivotal component for next-generation interactive avatars and virtual assistant

Enhancing Ultra-low-field MRI with Segmentation-guided Adversarial Learning

arXiv:2605.28016v1 Announce Type: new Abstract: Ultra-low-field (ULF) MRI offers portable and low-cost imaging but suffers from poor image quality. To address this, we present our submission to the 20

Extracting Small Translation Specialists from LLMs by Aggressively Pruning Experts

arXiv:2605.28042v1 Announce Type: cross Abstract: Modern large language models (LLMs) achieve state-of-the-art machine translation performance, but they do so as broad generalists largely trained for

researcharxiv-cs-ai