Search: “models”

arXiv:2507.06219v2 Announce Type: replace Abstract: Data scaling has driven remarkable success in foundation models for Natural Language Processing (NLP) and Computer Vision (CV), yet the principles o

safetyarxiv-cs-ro

LANTERN: Layered Archival and Temporal Episodic Retrieval Network for Long-Context LLM Conversations

DGX agent

arXiv:2606.05182v1 Announce Type: new Abstract: Large language models discard critical details when conversation history is compacted to fit within finite context windows. We present LANTERN (Layered

applicationsarxiv-cs-cl

5 Jun 2026

LLM-Guided ANN Index Optimization for Human-Object Interaction Retrieval

arXiv:2606.05489v1 Announce Type: new Abstract: Retrieval systems underpin modern AI applications -- spanning visual search, recommendation engines, and multi-modal question answering. Modern multi-st

MAviS: A Multimodal Conversational Assistant For Avian Species

arXiv:2603.07294v2 Announce Type: replace Abstract: Fine-grained understanding and species-specific multimodal question answering are vital for advancing biodiversity conservation and ecological monit

Mechanistic Insights into Functional Sparsity in Multimodal LLMs via CoRe Heads

arXiv:2606.05843v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) demonstrate remarkable proficiency on complex vision-language tasks, the mechanisms by which they extract

local-aiarxiv-cs-cl

Applications

OneReason Technical Report

arXiv:2606.06260v1 Announce Type: cross Abstract: Generative recommendation models in the OneRec family have been widely deployed in many real-world services, such as short-video, live-streaming, adve

applicationsarxiv-cs-cl

PAR3D: A Unified 3D-MLLM with Part-Aware Representation for Scene Understanding

arXiv:2606.06485v1 Announce Type: new Abstract: Recent advances in 3D multimodal large language models (3D-MLLMs) have enabled unified solutions for 3D scene understanding tasks, including visual ques

Physics in 2-Steps: Locking Motion Priors Before Visual Refinement Erases Them

arXiv:2606.06361v1 Announce Type: new Abstract: Image-to-Video diffusion models leverage input images to generate visually stunning content, yet frequently produce motion that violates physical laws.

Predictable Scaling Laws of Optimal Hyperparameters for LLM Continued Pre-training

arXiv:2606.05610v1 Announce Type: new Abstract: The efficacy of continued pre-training for Large Language Models (LLMs) hinges upon hyperparameter configurations, such as learning rate and batch size.

ProSarc: Prosody-Aware Sarcasm Recognition Framework via Temporal Prosodic Incongruity

arXiv:2606.06168v1 Announce Type: cross Abstract: We present ProSarc, an audio-only framework that detects sarcasm by modelling temporal prosodic incongruity, that is, the mismatch between local proso

local-aiarxiv-cs-cl

Representing Research Attention as Contextually Structured Flows

arXiv:2606.05895v1 Announce Type: new Abstract: Research attention is widely used as an indicator of visibility, influence, and societal uptake, yet it is typically represented as aggregated counts th

Rethinking LoRA Memory Through the Lens of KV Cache Compression

arXiv:2606.05698v1 Announce Type: new Abstract: Parametric retrieval augmentation encodes document information into lightweight, document-specific modules such as LoRA adapters, reducing the need to i

Ten Headache Specialists versus Artificial Intelligence for Clinical Literature Summarization: A Critical Evaluation and Comparison

arXiv:2606.05436v1 Announce Type: cross Abstract: Summarizing the latest medical literature to guide clinical decision-making is essential for evidence-based medicine and high-quality patient care. Ye

Token costs are why there will be no saas apocalypse / good dev tools are cached intelligence for agents! The popular theory goes: agents ca…

model-releasesclem-delangue--x

Token costs are why there will be no saas apocalypse / good dev tools are cached intelligence for agents! The popular theory goes: agents can write code, so they'll just rebuild every tool from scratc

Towards One-to-Many Temporal Grounding

arXiv:2606.06294v1 Announce Type: new Abstract: Temporal Grounding (TG) aims to localize video segments corresponding to a textual query. Prior research predominantly focuses on single-segment retriev

Unlocking dependable responses with Gemini Enterprise Agent Platform’s Agentic RAG

model-releasesgoogle-research

Google's RAG Engine securely connects private enterprise data to LLMs to improve answer accuracy and reduce hallucinations , making it a key component of the Gemini Enterprise Agent Platform for build

Unsupervised Monocular 3D Keypoint Discovery from Multi-View Diffusion Priors

arXiv:2507.12336v2 Announce Type: replace Abstract: Most existing 3D keypoint estimation methods rely on manual annotations or calibrated multi-view images, both of which are expensive to collect. Thi

USAD 2.0: Scaling Representation Distillation for Universal Audio Understanding

arXiv:2606.06444v1 Announce Type: cross Abstract: Audio encoders are critical to modern audio applications as large language models (LLMs) increasingly rely on a single encoder for diverse inputs. Whi

VASO: Formally Verifiable Self-Evolving Skills for Physical AI Agents

arXiv:2606.05395v1 Announce Type: new Abstract: Reusable robot skills are becoming the basic units through which embodied agents turn open-ended instructions into long-horizon physical behavior. We ar

local-aiarxiv-cs-ro

Video-Rate Streaming Stylization on a Vision-Aware MLLM-Conditioned Edit Diffusion: Asymmetric Batched Inference on a Distilled UNet + MLLM Text Encoder

arXiv:2606.05981v1 Announce Type: new Abstract: Aggressive distillation of the diffusion U-Net inverts the per-frame bottleneck of real-time text-to-image pipelines: once the denoiser is a 4-step or 1

VideoKR: Towards Knowledge- and Reasoning-Intensive Video Understanding

arXiv:2606.05259v1 Announce Type: new Abstract: We introduce VideoKR, the first large-scale training corpus specifically designed to strengthen knowledge- and reasoning-intensive video understanding.

Vision Hopfield Memory Networks

arXiv:2603.25157v2 Announce Type: replace-cross Abstract: Recent vision and multimodal foundation backbones, such as Transformer families and state-space models like Mamba, have achieved remarkable pr

local-aiarxiv-cs-cv

Visual Commonsense Driven Knowledge Refinements for Scene Graph Generation

arXiv:2606.06369v1 Announce Type: new Abstract: Learning-driven Scene Graph Generation (SGG) models excel on frequent relation types but degrade sharply under annotation sparsity, failing to capture r

VTI-CoT: Visual-Textual Interleaved Chain of Thought for Video Reasoning

arXiv:2606.05736v1 Announce Type: new Abstract: Video reasoning aims to understand complex temporal events and causal relationships within videos. Recently, Chain-of-Thought (CoT) has been introduced

We've made a breakthrough in self-evolving AI scientists moving from 'search' to 'principled discovery': Scientific discovery requires that …

model-releasesgary-marcus--x

We've made a breakthrough in self-evolving AI scientists moving from 'search' to 'principled discovery': Scientific discovery requires that the search space itself changes, and an AI scientist must pe

Your AI chatbot is only as good as the data behind it. This n8n template from our friends at @apify shows you how to wire up a RAG pipeline …

model-releasespinecone--x

Your AI chatbot is only as good as the data behind it. This n8n template from our friends at @apify shows you how to wire up a RAG pipeline using Apify + Pinecone + Gemini so your chatbot can answer q

Affordance2Action: Task-Conditioned Scene-level Affordance Grounding for Real-Time Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.04172v1 Announce Type: new Abstract: Task-conditioned manipulation requires grounding instructions to task-relevant functional parts rather than object categories. This setting is scene-dep

Agent Planning Benchmark: A Diagnostic Framework for Planning Capabilities in LLM Agents

arXiv:2606.04874v1 Announce Type: new Abstract: Planning is central to LLM agents: before acting, an agent must decompose goals, select tools, reason over constraints, and decide when a task is infeas

ALINC: Active Learning for Inductive Node Classification via Graph Sampling

model-releasesarxiv-cs-lg

arXiv:2606.04647v1 Announce Type: new Abstract: Active learning (AL) for node classification typically focuses on selecting the most informative nodes for annotation within one or a few large graphs (

Andon Labs' Real-World AI Evals: Claude calls the FBI, AI CEOs, price cartels, Butter-Bench, & Luna https://latent.space/p/andon @andonlabs …

Andon Labs' Real-World AI Evals: Claude calls the FBI, AI CEOs, price cartels, Butter-Bench, & Luna https://latent.space/p/andon @andonlabs cofounders @lukaspet and @axelbacklund explain why dollar-de

model-releasesswyx--x

Benchmarking Living-Screen-Native GUI Agents on Short-Video Platforms

arXiv:2606.04701v1 Announce Type: cross Abstract: GUI agents today assume a static screen, where the world is frozen between two actions. However, real interfaces such as short-video applications viol

Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability

model-releasesarxiv-cs-lg

arXiv:2606.04754v1 Announce Type: new Abstract: Many striking phenomena in deep learning, such as linear mode connectivity and the structured behavior of training dynamics, are closely tied to paramet

Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification?

arXiv:2506.10912v4 Announce Type: replace Abstract: Toxicity remains a leading cause of early-stage drug development failure. Despite advances in molecular design and property prediction, the task of

Can Generalist Agents Automate Data Curation?

arXiv:2606.04261v1 Announce Type: new Abstract: Curating training data is among the most consequential yet labor-intensive parts of modern AI development: practitioners iteratively propose, implement,

Can Reasoning Path still be Effective as Input? Bridging Post-Reasoning to Chain-of-Thought Compression

arXiv:2510.08647v2 Announce Type: replace-cross Abstract: Recent developments have enabled advanced reasoning in Large Language Models (LLMs) via long Chain-of-Thought (CoT), trading efficiency during

researcharxiv-cs-ai

CDPM-Align: Multi-Scale Guidance-Aligned Diffusion Pretraining for Robust Few-Shot Anatomical Landmark Detection

arXiv:2606.04898v1 Announce Type: new Abstract: Anatomical landmark detection is a fundamental task in medical image analysis supporting a wide range of diagnostic and interventional workflows. Althou

ChannelTok: Efficient Flexible-Length Vision Tokenization

arXiv:2606.04461v1 Announce Type: new Abstract: Leading flexible vision tokenizers achieve SOTA quality at an extreme cost, relying on parameter-heavy backbones and slow, multi-step generative decoder

Tutorials

Characterizing, Evaluating, and Optimizing Complex Reasoning

arXiv:2602.08498v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) increasingly rely on reasoning traces with complex internal structures. However, existing work lacks a unified answer

tutorialsarxiv-cs-cl

ChatSOP: An SOP-Guided MCTS Planning Framework for Controllable LLM Dialogue Agents

arXiv:2407.03884v4 Announce Type: replace-cross Abstract: Dialogue agents powered by Large Language Models (LLMs) show superior performance in various tasks. Despite the better user understanding and

researcharxiv-cs-ai

Computational conceptual history of scientific concepts: From early digital methods to LLMs

arXiv:2606.04118v1 Announce Type: new Abstract: This article situates large language models (LLMs) within the longer history of computational approaches to concept analysis in the history, philosophy,

Safety

Confidence Before Answering: A Paradigm Shift for Efficient LLM Uncertainty Estimation

arXiv:2603.05881v2 Announce Type: replace Abstract: Reliable deployment of large language models (LLMs) requires accurate uncertainty estimation. Existing methods are predominantly answer-first, produ

safetyarxiv-cs-cl

Constraint-Enhanced Physical Search through Correlation Matching

arXiv:2606.03554v1 Announce Type: cross Abstract: Physical systems do not merely add noise to search processes; they impose constraints that generate structured correlations. We propose a principle of

Cross-Prompt Generalization in Detecting AI-Generated Fake News Using Interpretable Linguistic Features

arXiv:2606.04199v1 Announce Type: new Abstract: The increasing use of large language models has raised concerns about the spread of AI-generated fake news, particularly under varying prompting strateg

D^3-MoE:Dual Disentangled Diffusion Mixture-of-Experts for Style-Controllable End-to-End Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2606.04884v1 Announce Type: new Abstract: Traditional end-to-end autonomous driving frameworks frequently suffer from the 'style-averaging' dilemma when trained on high-variance human demonstrat

DLLG: Dynamic Logit-Level Gating of LLM Experts

arXiv:2606.04378v1 Announce Type: new Abstract: Leveraging multiple specialized LLMs can combine complementary strengths, but existing approaches trade adaptability for stability: routing commits prem

DLO-Lab: Benchmarking Deformable Linear Object Manipulations with Differentiable Physics

model-releasesarxiv-cs-ro

arXiv:2606.04206v1 Announce Type: new Abstract: We address the challenge of enabling robots to manipulate deformable linear objects (DLOs), such as ropes, cables, and rubber bands. Prior work has prim

Emotion Entanglement and Bayesian Inference for Multi-Dimensional Emotion Understanding

arXiv:2604.00819v2 Announce Type: replace-cross Abstract: Understanding emotions in natural language is inherently a multi-dimensional reasoning problem, where multiple affective signals interact thro

From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agents

arXiv:2606.04329v1 Announce Type: cross Abstract: Memory is a core component of AI agents, enabling them to accumulate knowledge across interactions and improve performance. However, persistent memory