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arXiv:2606.30653v1 Announce Type: cross Abstract: Large language models are increasingly deployed in agentic pipelines that depend on the model evaluating its own outputs without external verification

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🔬 The Coolest Diffusion Research Isn't in LLMs — Evan Feinberg & Sergey Edunov, Genesis Molecular AI

DGX agent

This episode discusses cutting-edge diffusion model research applications beyond large language models, featuring insights from Evan Feinberg and Sergey Edunov of Genesis Molecular AI on how diffusion

model-releaseslatent-space

1 Jul 2026

Theory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and Action

model-releasesarxiv-cs-cl

arXiv:2606.31916v1 Announce Type: new Abstract: Theory of Mind (ToM) benchmarks for Large Language Models (LLMs) typically rely on passive question-answering formats, but the deployment of LLMs in inc

Think in English, Answer in Korean: Efficient Adaptation of Multilingual Tool-Using Agents

arXiv:2606.31648v1 Announce Type: new Abstract: We present LuckyStar 111B, a 111B-parameter hybrid reasoning model developed through a collaboration between Cohere and LG CNS for Korean-English enterp

Towards a foundational model for recognising diastematic Gregorian notation

arXiv:2606.31454v1 Announce Type: new Abstract: Optical recognition of Gregorian notation has recently been attempted with end-to-end methods, with four datasets introduced. However, each of these dat

TreeAgent: A Generalizable Multi-Agent Framework for Automated Bias Labeling in Forestry via Compiled Expert Rules and Vision-Language Models

arXiv:2606.31976v1 Announce Type: new Abstract: Human-labeled data are widely used as reference annotations in ML, despite known variability across annotators in many expert-driven domains. In additio

safetyarxiv-cs-ai

Vision-Language Procedural Reasoning for Context-Aware Reward Modeling of Robotic Endovascular Guidewire Navigation

arXiv:2606.30698v1 Announce Type: new Abstract: Robotic-assisted endovascular interventions demand accurate, stable, and context-aware guidewire navigation in complex and patient-specific vascular ana

safetyarxiv-cs-ro

When Calibration Rankings Reverse: Accuracy-Controlled Evaluation for Fair Comparison of LLMs

arXiv:2606.30814v1 Announce Type: new Abstract: Calibration evaluates whether a model confidence aligns with its empirical accuracy. Existing studies often compare the calibration of different large l

When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors

arXiv:2606.32029v1 Announce Type: cross Abstract: While large language models (LLMs) perform well on table tasks, they still make data referencing errors (DREs), i.e., incorrectly citing or omitting t

When Sinks Help or Hurt: Unified Framework for Attention Sink in Large Vision-Language Models

arXiv:2604.03316v2 Announce Type: replace Abstract: Attention sinks are defined as tokens that attract disproportionate attention. While these have been studied in single modality transformers, their

When the Database Fails: Prompting LLM Dialogue Agents for Safe Recovery in Task-Oriented Dialogue

model-releasesarxiv-cs-cl

arXiv:2606.31307v1 Announce Type: new Abstract: Large language models used in task-oriented dialogue often produce fluent but unsafe responses when backend database calls fail, return empty results, o

Applications

AEGIR: Modeling Area Emitters for Indoor Inverse Rendering using Gaussian Splatting

arXiv:2606.28635v1 Announce Type: new Abstract: Inverse rendering requires separating illumination from surface materials, which is highly ambiguous due to their tight coupling in observed images. Whi

applicationsarxiv-cs-cv

AnTenA: Actionable and Explainable Tensor Analysis System with Large Language Models

arXiv:2606.28708v1 Announce Type: new Abstract: Accurately explaining hidden patterns in multi-aspect data has typically been done by leveraging labels and/or accompanying auxiliary metadata. However,

Audio-Visual Continual Test-Time Adaptation without Forgetting

model-releasesarxiv-cs-lg

arXiv:2602.18528v2 Announce Type: replace Abstract: Audio-visual continual test-time adaptation involves continually adapting a source audio-visual model at test-time, to unlabeled non-stationary doma

Tutorials

Before Thinking, Learn to Decide: Proactive Routing for Efficient Visual Reasoning

arXiv:2606.30217v1 Announce Type: new Abstract: Large multimodal models have achieved strong reasoning on complex visual tasks, but their inference efficiency is often restricted by long chains of tho

tutorialsarxiv-cs-cl

Beyond Scaling Law: A Data-Efficient Distillation Framework for Reasoning

arXiv:2508.09883v2 Announce Type: replace-cross Abstract: Large language models (LLMs) demonstrate remarkable reasoning capabilities in tasks such as algorithmic coding and mathematical problem-solvin

Build agents even faster with Gemini Enterprise Agent Platform’s fully-managed, remote MCP server

model-releasesgoogle-cloud-ai

A couple of months ago, we announced that over 50 Google-managed MCP servers are available. Today, we’ll dive into how to use the Gemini Enterprise Agent Platform remote MCP server to securely connect

Closing the Activation-Cone Blind Spot: Response-Time Probing and Unified Defense

arXiv:2606.29441v1 Announce Type: cross Abstract: Inference-time safety methods for large language models have proliferated, yet no systematic comparison exists. We evaluate five defense paradigms (no

DeVAR: Low-Dose CT Denoising via Visual Autoregressive Modeling

arXiv:2606.28453v1 Announce Type: cross Abstract: Computed tomography (CT) plays a crucial role in medical diagnosis, but minimizing radiation exposure while maintaining image quality remains a critic

Diff-Based Code Corruption using LLMs for Large-Scale Bugfix Benchmarking

arXiv:2606.29088v1 Announce Type: cross Abstract: There are various benchmarks to evaluate bugfixing capabilities of Large Language Models. However, most widespread benchmarks do not fully reflect rea

Distribution Matching Variational AutoEncoder

arXiv:2512.07778v2 Announce Type: replace Abstract: Most visual generative models compress images into a latent space before applying diffusion or autoregressive modelling. Yet, existing approaches su

safetyarxiv-cs-cv

EMPATH: A Multilingual Auditor-Judge Benchmark for Safety Evaluation of Emotional-Support Chatbots

arXiv:2606.30256v1 Announce Type: new Abstract: Safety benchmarks often buy scalability by fixing the prompt, the language, and the turn structure. For emotional-support chatbots, that bargain hides p

FinInvest-GTCN: Explainable Graph-Temporal-Causal Modeling for Risk-Aware Investment Decision Optimization

arXiv:2606.28933v1 Announce Type: new Abstract: Venture capital (VC) investment decisions face distinct challenges, such as multi-source heterogeneous data, non-stationary time series, and the demand

From Tool Connection to Execution Control: Benchmarking Security Invariants in MCP-Style Agent Runtimes

arXiv:2606.29073v1 Announce Type: cross Abstract: Model Context Protocol (MCP)-style ecosystems give language-model applications a practical connection layer for tools, resources, prompts, and transpo

Generative Large Language Models in Automated Fact-Checking: A Survey

arXiv:2407.02351v3 Announce Type: replace Abstract: The rapid spread of false and misleading information on online platforms poses a growing societal challenge, overwhelming the capacity of manual fac

GPTNT: Benchmarking Real-Time Collaboration Between Multimodal Agents on Keep Talking And Nobody Explodes

arXiv:2606.28514v1 Announce Type: new Abstract: Multimodal models are increasingly deployed to solve tasks collaboratively with humans or other artificial agents. Existing benchmarks show that these m

High-Resolution Climate Projections Using Diffusion-Based Downscaling of a Lightweight Climate Emulator

arXiv:2602.13416v2 Announce Type: replace Abstract: The proliferation of data-driven models in weather and climate sciences has marked a significant paradigm shift, with advanced models demonstrating

researcharxiv-cs-lg

How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation

arXiv:2606.28358v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) aims to enhance the trustworthiness of Large Language Models (LLMs) by grounding their outputs in external docume

HSAP: A Hierachical Sequence-aware Parallelism for Hybrid-Context Generative Models

arXiv:2606.30460v1 Announce Type: new Abstract: In this paper, we aim to combine the advantages of existing sequence parallelism paradigms and overcomes their drawbacks, the most serious of which is t

researcharxiv-cs-lg

LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion

model-releasesarxiv-cs-cv

arXiv:2603.14526v2 Announce Type: replace Abstract: The recent success of inference-time scaling in large language models has inspired similar explorations in video diffusion. In particular, motivated

MCP Server Architecture Patterns for LLM-Integrated Applications

arXiv:2606.30317v1 Announce Type: cross Abstract: The Model Context Protocol (MCP), introduced by Anthropic in November 2024, defines a standardized interface for connecting large language models (LLM

MemDelta: Controlled Baselines and Hidden Confounds in Agent Memory Evaluation

model-releasesarxiv-cs-cl

arXiv:2606.29914v1 Announce Type: new Abstract: Agent memory systems are increasingly evaluated against RAG and full-context baselines, but reported gains often mix changes in the memory method with c

Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models

arXiv:2603.18907v2 Announce Type: replace Abstract: We propose a new Neural Galerkin Normalizing Flow framework to approximate the transition probability density function of a diffusion process by sol

researcharxiv-cs-lg

Applications

On Surrogate Modeling of Static Response of AM Short-Fiber Thermoplastics Using Graph Neural Networks

arXiv:2606.28996v1 Announce Type: new Abstract: Short-fiber thermoplastic (SFT) composites are increasingly employed in lightweight aerospace and automotive structures owing to their favorable strengt

applicationsarxiv-cs-lg

Overcoming Dependent Censoring in the Evaluation of Survival Models

arXiv:2502.19460v4 Announce Type: replace-cross Abstract: Dependent censoring occurs when the event time and censoring time are not conditionally independent given the observed covariates. This compli

researcharxiv-cs-ai

Start building with Nano Banana 2 Lite and Gemini Omni Flash

model-releasesgoogle-deepmind

Nano Banana 2 Lite is Google's fastest and most cost-efficient image generation model, generating images in approximately 4 seconds , while Gemini Omni Flash is a multimodal model supporting high-qual

STEAM: Self-Supervised Temporal Ensemble Advantage Modeling for Real-World Robot Learning

arXiv:2606.29834v1 Announce Type: new Abstract: Real-world robot learning increasingly relies on heterogeneous data, but demonstrations and rollouts often mix useful progress with stalls, corrections,

safetyarxiv-cs-ro

SVCBench: A Streaming Video Counting Benchmark for Spatial-Temporal State Maintenance

model-releasesarxiv-cs-cv

arXiv:2603.12703v3 Announce Type: replace Abstract: Video understanding requires models to continuously track and update world state during playback. Although existing benchmarks have advanced video u

Tutorials

T2LDM++: A Self-Conditioned Representation Guided Diffusion Model for Realistic Text-to-LiDAR Scene Generation

arXiv:2606.30147v1 Announce Type: new Abstract: Recent progress in Text-to-Image generation benefits from large-scale Text-Image pairs. However, the scarcity of Text-LiDAR pairs often causes over-smoo

tutorialsarxiv-cs-cv

The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning

arXiv:2606.28843v1 Announce Type: cross Abstract: Fine-tuning a large language model is a ubiquitous method for enhancing its capability on a specific downstream task. However, prior work has shown th

TRACE: A Concept Bottleneck Model for Longitudinal 3D Glioblastoma Response Assessment

arXiv:2606.30313v1 Announce Type: new Abstract: Longitudinal glioblastoma response assessment requires comparing subtle tumor changes across MRI time points using structured clinical criteria such as

Vision-Language Models for Deployable Social Robot Navigation: Bridging Semantic Reasoning and Low-Level Control

arXiv:2606.28760v1 Announce Type: new Abstract: Social robot navigation (SRN) requires more than geometric path planning; it demands understanding human intentions, social norms, and contextual cues t

safetyarxiv-cs-ro

We are making a deliberate effort to use GLM 5.2 with OpenCode internally at Jarvislabs. I have spoken to 3 enterprise customers last week, …

model-releasesclem-delangue--x

We are making a deliberate effort to use GLM 5.2 with OpenCode internally at Jarvislabs. I have spoken to 3 enterprise customers last week, who are exploring to host multiple open source models and mo

Applications

COCOLogic-V2: Identifying Logical Inconsistencies via Truly Hard-Negatives

arXiv:2606.28194v1 Announce Type: new Abstract: While interpretable models such as concept bottleneck models (CBMs) and program synthesis methods enable verification of model decisions, their evaluati

applicationsarxiv-cs-lg

Agents

Orientation Matters: Learning Radiation Patterns of Multi-Rotor UAVs In-Flight to Enhance Communication Availability Modeling

arXiv:2604.02827v2 Announce Type: replace Abstract: The paper presents an approach for learning antenna Radiation Patterns (RPs) of a pair of heterogeneous quadrotor Uncrewed Aerial Vehicles (UAVs) by

agentsarxiv-cs-ro

PixelU: A U-Shaped Transformer for Efficient End-to-End Pixel Diffusion

arXiv:2606.27760v1 Announce Type: new Abstract: End-to-end pixel-space diffusion models bypass the lossy compression of Latent Diffusion Models (LDMs) but struggle to jointly model low-frequency seman

Supersede: Diagnosing and Training the Memory-Update Gap in LLM Agents

arXiv:2606.27472v1 Announce Type: cross Abstract: Large language model (LLM) agents operate over long, multi-session interactions in which facts change: a user moves, a price updates, a plan is revise

The Simulacrum: Decision-Theoretic Pretraining for Near-Optimal Time-Series Forecasting and Inference

arXiv:2606.27711v1 Announce Type: cross Abstract: We introduce a neural network-based framework for learning time series estimators through a process we term decision-theoretic pretraining. Analysts s