Search: “benchmark”

Concept Removal Guidance: Evidence-Calibrated Negative Guidance for Safe Diffusion Sampling

arXiv:2606.29801v1 Announce Type: new Abstract: Text-to-image diffusion models remain vulnerable to adversarial prompts that elicit disallowed content, motivating reliable inference-time controls. A p

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Consistency as Inductive Bias: Learning Cross-View Invariance for Robust Multimodal Reasoning

DGX agent

arXiv:2606.29812v1 Announce Type: new Abstract: Inductive biases steer learning toward generalizable solutions by encoding task structure. In this work, we identify a crucial missing bias in MLLMs: cr

safetyarxiv-cs-cv

30 Jun 2026

Conversational Query Engine for Mixed-Modality Heterogeneous Enterprise Data Sources

arXiv:2606.28370v1 Announce Type: cross Abstract: Enterprise business intelligence queries span structured warehouses and unstructured document repositories -- modalities with fundamentally different

Cool new paper from NVIDIA. Looks like agentic coding is moving into hardware design. HORIZON treats hardware design as repository-level cod…

Cool new paper from NVIDIA. Looks like agentic coding is moving into hardware design. HORIZON treats hardware design as repository-level code evolution. A Markdown harness becomes a project pack with

model-releasesdair-ai--x

CORTEX: High-Quality Cross-Domain Organization of Web-Scale Corpora through Ontological Corpus Graph

arXiv:2606.30175v1 Announce Type: new Abstract: The continuous evolution of large language models drives escalating demands on data scale and quality, and as different training stages impose increasin

CoSPlan: Corrective Sequential Planning via Scene Graph Incremental Updates

arXiv:2512.10342v3 Announce Type: replace Abstract: Vision Language Models (VLMs) have shown promising planning capabilities, yet their success remains confined to the text domain, leaving visual deci

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

arXiv:2511.02734v3 Announce Type: replace Abstract: Current evaluations of Large Language Model (LLM) agents primarily emphasize task completion, often overlooking resource efficiency and adaptability

Counterfactual Residual Data Augmentation for Regression

arXiv:2606.28460v1 Announce Type: cross Abstract: Data-driven modeling in real-world regression tasks often suffers from limited training samples, high collection costs, and noisy observations. Inspir

Covering the Unseen: Information Demand Coverage Optimization for Retrieval-Augmented Generation

arXiv:2606.29328v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) typically treats context selection as ranking chunks against a single query embedding. This assumption breaks dow

CrossWeaver: Cross-modal Weaving for Arbitrary-Modality Semantic Segmentation

arXiv:2604.02948v2 Announce Type: replace Abstract: Multimodal semantic segmentation has shown great potential in leveraging complementary information across diverse sensing modalities. However, exist

CubifyGS: Object-Centric 3D Gaussian Splatting for Lifelong Dynamic Scene Maintenance

model-releasesarxiv-cs-ro

arXiv:2606.28720v1 Announce Type: new Abstract: Lifelong scene mapping under rigid object rearrangement remains a fundamental challenge in robotics. While 3D Gaussian Splatting (3DGS) enables high-fid

Curvature-Guided Sheaf Diffusion for Unsupervised Community Detection on Heterophilic Graphs

arXiv:2606.30249v1 Announce Type: cross Abstract: Detecting communities in heterophilic graphs -- where connected nodes often belong to different classes -- is hard for unsupervised methods: classical

Agents

DAIN: Dynamic Agent-Based Interaction Network for Efficient and Collaborative Multimodal Reasoning

arXiv:2606.30189v1 Announce Type: new Abstract: Current multimodal fusion approaches, particularly those based on static Mixture-of-Experts (MoE) architectures, often struggle to provide the adaptive

agentsarxiv-cs-cl

Defeat Devices in AI Systems

arXiv:2606.28863v1 Announce Type: cross Abstract: AI systems increasingly exhibit behavior that differs systematically between evaluation and deployment contexts. Alignment faking, sandbagging, benchm

DefenseSplat: Enhancing the Robustness of 3D Gaussian Splatting via Frequency-Aware Filtering

arXiv:2602.19323v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful paradigm for real-time and high-fidelity 3D reconstruction from posed images. However, recent

Delayed Bidirectional Alignment via Disentangled Audio Semantics for Audio-Visual Segmentation

arXiv:2512.20117v2 Announce Type: replace Abstract: Audio-Visual Segmentation (AVS) aims to localize sound-producing objects at the pixel level by integrating auditory and visual cues. However, existi

Demonstration-Free Robotic Control via LLM Agents

arXiv:2601.20334v2 Announce Type: replace-cross Abstract: Robotic manipulation has increasingly adopted vision-language-action (VLA) models, which achieve strong performance but typically require task

Diagnosing and Mitigating Context Rot in Long-horizon Search

arXiv:2606.29718v1 Announce Type: cross Abstract: Extensive context has become the norm as Large Language Models (LLMs) are increasingly deployed in long-horizon tasks. The concern that increasing con

DialogPII: A multilingual dataset of synthetic dialog transcripts to detect personal information

arXiv:2606.30312v1 Announce Type: new Abstract: Conversational data collected in domains such as healthcare or social sciences is a valuable resource for research and automated analysis. However, resp

Applications

DiLaServe: High SLO Attainment Serving for Diffusion Language Models

arXiv:2606.29094v1 Announce Type: new Abstract: Diffusion language models (DLMs) have recently emerged as a promising alternative to conventional autoregressive language models. By generating multiple

applicationsarxiv-cs-lg

DivAS: Interactive 3D Segmentation by Depth-Weighted Voxel Aggregation

arXiv:2601.04860v2 Announce Type: replace Abstract: Interactive 3D segmentation of a reconstructed scene should not require a representation-specific optimization loop. We observe that the recipe for

Diversity is the Strength of the AI Crowd

arXiv:2606.29661v1 Announce Type: new Abstract: Top AI forecasting systems are approaching superforecaster-level accuracy on future world events, but still rely primarily on off-the-shelf LLMs combine

DLR: Zero-Inference-Cost Latent Residuals for Low-Rank Pre-Training

arXiv:2606.28932v1 Announce Type: cross Abstract: Large language models have driven recent progress in language and multimodal AI, yet pre-training them at scale is prohibitively expensive. Low-rank p

DNA Language Models: An Assessment of Pre-Training for Fine-Tuning Tasks

arXiv:2606.30140v1 Announce Type: cross Abstract: Recent breakthroughs in foundation models and Large Language Models (LLMs) have introduced new opportunities for studying and decoding genomic sequenc

Dockerless: Environment-Free Program Verifier for Coding Agents

arXiv:2606.28436v1 Announce Type: cross Abstract: Program verifiers play a central role in training coding agents, including selecting trajectories for supervised fine-tuning (SFT) and providing rewar

Does Role Specialization Matter for Explanation Faithfulness in Mixture-of-Experts?

arXiv:2606.29613v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures have recently been extended with role-based mechanisms for interpretability. This is typically done by assignin

Domain-Informed Multi-View Self-Distillation for Astronomical Light-Curve Representation Learning with JEPA

arXiv:2606.28446v1 Announce Type: cross Abstract: Light curves describe temporal variations in the brightness of celestial objects. Learning robust representations of light curves is essential for lar

DTI: Dynamic Trajectory Initialization for Generative Face Video Super-Resolution

arXiv:2606.29198v1 Announce Type: new Abstract: As the most perceptually powerful Face Video Super-Resolution (FVSR) method, existing works in Generative FVSR (GFVSR) mainly exploit the generative pri

DuoMem: Towards Capable On-Device Memory Agents via Dual-Space Distillation

arXiv:2606.29961v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents can solve complex procedural tasks by interacting with environments over multiple turns, but this ability typi

Dynamic Parsing and Updating Natural Language Specification using VLMs for Robust Vision-Language Tracking

arXiv:2606.29357v1 Announce Type: cross Abstract: Vision-language tracking guided by natural language specifications leverages high-level semantic cues of target objects to substantially boost trackin

Early Estimation of Language to Latent Alignment in Diffusion Models

arXiv:2512.08505v2 Announce Type: replace Abstract: Conditional diffusion models frequently suffer from language-image misalignments. Due to the ambiguity of intermediate noise corrupted latents, asse

Early Warning Signals for OpenVLA Failure under Visual Distribution Shift

arXiv:2606.29699v1 Announce Type: cross Abstract: Vision Language Action models combine perception, language grounding, and control in a single policy, but their failures are hard to diagnose once vis

Efficient Retrieval-Augmented Generation via Token Co-occurrence Graphs

arXiv:2606.30093v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates hallucinations in Large Language Models (LLMs) by grounding the generation process on external knowledge.

researcharxiv-cs-cl

Efficient Visual Pointing for Embodied AI:Agent-Driven Data Synthesis, Cross-Block Attention, and Iterative Correction

arXiv:2606.29850v1 Announce Type: new Abstract: Visual pointing maps a language instruction to pixel co ordinates, a core skill for embodied AI. We describe our PointArena 2026 solution, which achieve

Agents

Efficient-VLN: A Simple yet Strong Baseline for Efficient Vision-Language Navigation

arXiv:2512.10310v2 Announce Type: replace Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated significant promise in Vision-Language Navigation (VLN), existing agents remain hea

agentsarxiv-cs-cv

Emergence of a Shared Canonical Object Frame from In-the-Wild Videos

arXiv:2606.30058v1 Announce Type: new Abstract: Comparing object orientations and positions across different instances requires their poses to be expressed in a shared canonical frame. Establishing su

Emergence of Minimal Circuits for Indirect Object Identification in Attention-Only Transformers

arXiv:2510.25013v2 Announce Type: replace-cross Abstract: Mechanistic interpretability aims to reverse-engineer large language models (LLMs) into human-understandable computational circuits. However,

Ensemble Learning Based Classification Algorithm Recommendation

arXiv:2101.05993v2 Announce Type: replace-cross Abstract: Selecting an appropriate classification algorithm for a given data set remains a challenging problem in data mining and machine learning. Exis

Entropy-Gated Latent Recursion

arXiv:2606.16620v2 Announce Type: replace-cross Abstract: Inference-time scaling has become the dominant lever for improving language-model reasoning, but existing methods derive rollout diversity fro

EventVLA: Event-Driven Visual Evidence Memory for Long-Horizon Vision-Language-Action Policies

arXiv:2606.20092v2 Announce Type: replace Abstract: Memory remains a critical bottleneck for long-horizon robotic manipulation, as standard Vision-Language-Action (VLA) policies often fail when task-r

EVLA: An Electro-Aware Multimodal Assistant for Physically-Grounded Driving Reasoning and Control

arXiv:2606.28938v1 Announce Type: new Abstract: Modern vision-language models (VLMs) for driving assistants typically treat vehicle dynamics as a black box, resulting in decisions that lack awareness

Evolutional Math: Cross-Validated Island-Model Genetic Programming for Interpretable Symbolic Regression on Small, Wide Datasets

arXiv:2606.28381v1 Announce Type: cross Abstract: Symbolic regression via genetic programming routinely fails on small, wide datasets - a regime common in clinical-trial monitoring, biostatistics, and

Experience Augmented Policy Optimization for LLM Reasoning

model-releasesarxiv-cs-lg

arXiv:2606.30420v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is a powerful paradigm for improving the reasoning capabilities of large language models (LLMs). H

Experience-Evolving Multi-Turn Tool-Use Agent with Hybrid Episodic-Procedural Memory

arXiv:2512.07287v3 Announce Type: replace-cross Abstract: As intents unfold and environments change, multi-turn agents face continuously shifting decision contexts. Although reusing past experience is

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Expert Evaluation of Clinical AI Tools on Real Point-of-Care Clinical Queries

arXiv:2606.28960v1 Announce Type: new Abstract: Physicians now pose millions of clinical questions to AI tools each week, yet these tools are evaluated largely on hypothetical or exam-style questions,

Explaining Attention with Program Synthesis

arXiv:2606.19317v2 Announce Type: replace-cross Abstract: A longstanding goal of research on interpretable deep learning is to replace opaque neural computations with human-meaningful symbolic descrip

Exploiting Local Flatness for Efficient Out-of-Distribution Detection

arXiv:2606.29952v1 Announce Type: cross Abstract: Detecting out-of-distribution (OOD) data is crucial for reliable machine learning deployment. Among detection strategies, post-hoc methods are particu

ExploreVLA: Dense World Modeling and Exploration for End-to-End Autonomous Driving

arXiv:2604.02714v2 Announce Type: replace Abstract: End-to-end autonomous driving models based on Vision-Language-Action (VLA) architectures have shown promising results by learning driving policies t