Search: “context”

PruneGround: Plug-and-play Spatial Pruning for 3D Visual Grounding

arXiv:2606.31148v1 Announce Type: cross Abstract: 3D Visual Grounding (3DVG) aims to localize target objects in 3D scenes given natural language descriptions. Existing approaches typically perform rea

local-aiarxiv-cs-ai

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Reinforcement Learning with Metacognitive Feedback Elicits Faithful Uncertainty Expression in LLMs

DGX agent

arXiv:2606.32032v1 Announce Type: cross Abstract: Metacognition is a critical component of intelligence that describes the ability to monitor and regulate one's own cognitive processes. Yet LLMs exhib

safetyarxiv-cs-ai

1 Jul 2026

REMSA: Foundation Model Selection for Remote Sensing via a Constraint-Aware Agent

arXiv:2511.17442v3 Announce Type: replace-cross Abstract: Foundation Models (FMs) are increasingly integrated into remote sensing (RS) pipelines. These models include unimodal vision encoders and mult

Robust 3D-Masked Part-level Editing in 3D Gaussian Splatting with Regularized Score Distillation Sampling

arXiv:2507.11061v3 Announce Type: replace-cross Abstract: Recent advances in 3D neural representations and instance-level editing models have enabled the efficient creation of high-quality 3D content.

local-aiarxiv-cs-ai

Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings

arXiv:2606.31602v1 Announce Type: new Abstract: This work presents Dual-Embedding Watermarking (DEW), a semantic watermarking scheme for large language models (LLMs) that leverages contextual and toke

safetyarxiv-cs-cl

Scientific Explanations in Health Sciences: Causality, Trust, and Epistemic Adequacy

arXiv:2606.31616v1 Announce Type: new Abstract: Medical Artificial Intelligence (AI) is widely expected to transform clinical practice, yet the decision-making processes of many Machine Learning (ML)

Seeing Is Not Sharing: Some Vision-Language Models Overestimate Common Ground in Asymmetric Dialogue

arXiv:2606.31719v1 Announce Type: cross Abstract: In collaborative dialogue, shared perception does not guarantee shared interpretation. Mutual understanding must be established through interaction. W

Agents

ShopX: A Foundation Model for Intent-to-Item Fulfillment in Agentic Shopping

arXiv:2606.31693v1 Announce Type: cross Abstract: The wave of AI-native applications is moving shopping beyond page- and feed-based browsing toward intent-driven experiences orchestrated by LLM agents

agentsarxiv-cs-ai

SimpleSearch-VL: A Simple Recipe for Multimodal Agentic Deep Search

model-releasesarxiv-cs-cv

arXiv:2606.31504v1 Announce Type: new Abstract: We present SimpleSearch-VL, an efficient, reliable, and practical framework for multimodal agentic search. Its core idea is to improve the agent's own s

SOCRadar powers rapid threat detection with AlloyDB and Gemini Enterprise

model-releasesgoogle-cloud-ai

Editor’s note: SOCRadar is a leading cybersecurity company that provides threat intelligence to businesses worldwide. As the volume of cyber threats continued to grow, SOCRadar needed to modernize its

Tutorials

Step-by-Step Video-to-Audio Synthesis via Negative Audio Guidance

arXiv:2506.20995v4 Announce Type: replace Abstract: We propose a step-by-step video-to-audio (V2A) generation method that provides finer control over the generation process and more realistic audio sy

tutorialsarxiv-cs-cv

Temporal Preservation over Processing: Diagnosing and Designing Spatiotemporal Single-Stage Video Detectors

arXiv:2606.31421v1 Announce Type: cross Abstract: Single-stage video object detectors are increasingly deployed in time-critical applications, yet it remains unclear whether these models genuinely rea

The Bidirectional Process Reward Model

model-releasesarxiv-cs-cl

arXiv:2508.01682v3 Announce Type: replace Abstract: Process Reward Models (PRMs), which assign fine-grained scores to intermediate reasoning steps within a solution trajectory, have emerged as a promi

The Label Imitation Game: Turing Test Network for Zero-Shot Pseudo-Label Pruning

arXiv:2606.30875v1 Announce Type: cross Abstract: Foundation model pseudo-labeling - labeling data strictly via zero-shot inference - enables massive scale, but performance is undermined by hallucinat

Thinking Before Retrieving: Robust Zero-Shot Composed Image Retrieval via Strategic Planning and Self-Criticism

arXiv:2606.31222v1 Announce Type: new Abstract: Composed image retrieval requires identifying a target image from a gallery by integrating a reference image with a textual modification instruction. In

Agents

We call ours Operational Language Wiki, essentially a pattern for building memory to fill in the delta between the “dialect” of a team vs th…

We call ours Operational Language Wiki, essentially a pattern for building memory to fill in the delta between the “dialect” of a team vs the “world language” that the LLM is trained on. Use it to cap

agentsharrison-chase--x

What Counts as an Error? Dual-Reference Benchmarking for Atypical ASR

model-releasesarxiv-cs-cl

arXiv:2606.31112v1 Announce Type: new Abstract: ASR systems have been often reported to underperform on atypical speech. An often conflated compounding factor is the existence of two valid transcripti

5ting at SemEval-2026 Task 8: Strong End-to-End Multi-Turn RAG via LLM-Based Reranking and Faithfulness Control

arXiv:2606.28737v1 Announce Type: cross Abstract: We introduce 5ting, our system for the SemEval2026 Task 8 (MTRAGEval), which evaluates multi-turn Retrieval Augmented Generation (RAG) systems. Multi

Tools

A candid hallway track interview with the man himself - @swyx Mini Podcast if you will, he's told me about a huge milestone tomorrow, things…

A candid hallway track interview with the man himself - @swyx Mini Podcast if you will, he's told me about a huge milestone tomorrow, things that have surprised him about @aiDotEngineer and ... a few

toolsswyx--x

A multi-architecture study of specificity refinement and false-positive mechanism analysis in prostate MRI

model-releasesarxiv-cs-cv

arXiv:2606.29977v1 Announce Type: cross Abstract: Objectives: To characterize residual false positives in prostate MRI detection, and to evaluate a lightweight post-hoc refinement head for case-level

Adaptive Financial Transformer with Regime-Gated Attention for Stock Return Prediction

arXiv:2606.29347v1 Announce Type: cross Abstract: Adaptive Financial Transformer (AFT) is proposed for stock return prediction under non-stationary financial markets. The model incorporates a Market R

AERMANI-VLM: Structured Prompting and Reasoning for Aerial Manipulation with Vision Language Models

arXiv:2511.01472v2 Announce Type: replace Abstract: The rapid progress of vision--language models (VLMs) has sparked growing interest in robotic control, where natural language can express the operati

safetyarxiv-cs-ro

Agentic Abstention: Do Agents Know When to Stop Instead of Act?

arXiv:2606.28733v1 Announce Type: new Abstract: LLM agents are expected to act over multiple turns, using search, browsing interfaces, and terminal tools to complete user goals. Yet not every goal is

ANVIL: Anomaly-based Vulnerability Identification without Labelled Training Data

arXiv:2408.16028v4 Announce Type: replace-cross Abstract: Supervised-learning-based vulnerability detectors often fall short due to limited labelled training data. In contrast, Large Language Models (

researcharxiv-cs-lg

As a European, I don't understand how the sitting U.S. president—who has to pay $5 million to a woman he r@ped and defamed—can remain in off…

I can't provide a summary of this post without access to its actual content. The title appears to reference legal judgments involving a U.S. president, but I would need to verify the specific claims a

researchyann-lecun--x

BabyHuBERT: Multilingual Self-Supervised Learning for Segmenting Speakers in Child-Centered Long-Form Recordings

arXiv:2509.15001v3 Announce Type: replace-cross Abstract: Child-centered daylong recordings are essential for studying early language development, but existing speech models trained on clean adult dat

researcharxiv-cs-lg

Behavior Prompting Policy: Demonstrations as Prompts for Manipulation

arXiv:2606.30457v1 Announce Type: new Abstract: We study behavior prompting, a paradigm that enables robots to perform new tasks at inference time given a single human demonstration, which we call a b

safetyarxiv-cs-ro

BERTomelo: Your Portuguese Encoder Best Friend

arXiv:2606.28999v1 Announce Type: cross Abstract: Encoders have become the state of the art for multiple NLP tasks, especially those requiring deep contextual understanding. While multilingual models

Bringing speed and strong cost performance to the market with Gemini Omni Flash and Nano Banana 2 Lite

model-releasesgoogle-cloud-ai

Great creative happens when your tools move at the speed of your ideas. To help you create rich, reliable experiences while reducing regeneration time and costs, we’re adding two new models to Gemini

BTI-Net: Bidirectional Decoder-Level Task Interaction via Uncertainty-Aware Gating for Multi-Task Medical Image Analysis

arXiv:2606.29102v1 Announce Type: cross Abstract: Jointly learning to segment and classify medical images demands cross-task synergy, yet encoder-sharing architectures limit decoder reconstruction to

Carolina Guide: A Multi-Agent RAG System with Institutional Guardrails for Academic Policy Assistance

arXiv:2606.28360v1 Announce Type: cross Abstract: University students often struggle to navigate complex academic policies, leading to advising bottlenecks and delayed access to critical information.

Categorize Early, Integrate Late: Divergent Processing Strategies in Automatic Speech Recognition

arXiv:2601.06972v2 Announce Type: replace Abstract: In speech language modeling, two architectures dominate the frontier: the Transformer and the Conformer. However, it remains unknown whether their c

researcharxiv-cs-cl

Categorizing Mathematical Concepts with LLM Voting Ensembles in Mathswitch

arXiv:2606.28815v1 Announce Type: cross Abstract: Mathswitch is an open-source project that imports mathematical concept records from sources such as Wikidata, Wikipedia, MathWorld, Encyclopedia of Ma

CLIMP: Contrastive Language-Image Mamba Pretraining

arXiv:2601.06891v2 Announce Type: replace Abstract: Contrastive Language-Image Pre-training (CLIP) relies on Vision Transformers whose attention mechanism is susceptible to spurious correlations, and

CLMASP: Coupling Large Language Models with Answer Set Programming for Robotic Task Planning

arXiv:2406.03367v2 Announce Type: replace Abstract: Large Language Models (LLMs) possess extensive foundational knowledge and moderate reasoning abilities, making them suitable for general task planni

CLQT: A Closed-Loop, Cost-Aware, Strategy-Consistent Benchmark for Diagnostic Evaluation of LLM Portfolio-Management Agents

arXiv:2606.29771v1 Announce Type: new Abstract: LLM agents are increasingly cast as autonomous portfolio managers, and benchmarks have moved from financial question-answering to sequential trading. Ye

Collective cooperation without individual fidelity in LLM agents

arXiv:2606.30454v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as agents in simulations of social systems, yet it remains unclear when their behavior can be inter

Consensus Clustering of Free-Viewing Gaze Data: New Insights into Human-Information Interaction

arXiv:2606.30035v1 Announce Type: new Abstract: Free-viewing gaze data provides a rich, task-free window into human visual attention. Conventional exploratory data analysis of the data provides user a

CouCE: A Unified Causal Framework for Debiased Deep Metric Learning

arXiv:2606.30365v1 Announce Type: new Abstract: Deep Metric Learning (DML) often struggles with zero-shot generalization because standard objectives inherently capture what co-occurs rather than what

CRAFT: Counterfactual Credit Assignment from Free Sibling Rollouts for Self-Distilled Agentic Reinforcement Learning

arXiv:2606.29476v1 Announce Type: cross Abstract: Self-distilled agentic reinforcement learning augments trajectory-level reward with a token-level distillation loss, using as its teacher the same pol

Customized Generative AI Agent for Transportation Engineering Practice: A Development and Continued Pre-training Guideline

arXiv:2606.29014v1 Announce Type: new Abstract: Recent advancements in generative artificial intelligence (AI) and large language models (LLMs) have shown significant promise in automating complex rea

Data Provenance for Image Auto-Regressive Generation

arXiv:2606.28386v1 Announce Type: cross Abstract: Image autoregressive models (IARs) have recently demonstrated remarkable capabilities in visual content generation, achieving photorealistic quality a

DCSNet: Multiscale Feature Aggregation for Small Medical Object Segmentation with Detection-guided Hierarchical Cropping

arXiv:2606.28402v1 Announce Type: new Abstract: Small object segmentation in medical imaging is primarily hindered by class imbalance and inherent boundary complexity. Consequently, conventional globa

Depth-Staggered Fibonacci Spacing for Sparse Attention: Static Schedules Beat Learned Dilation and Extrapolate Where Dense Attention Fails

arXiv:2606.28560v1 Announce Type: new Abstract: We study sparse self-attention in which each query attends to a dense local window plus a set of Fibonacci-spaced offsets, with a per-layer scalar alpha

local-aiarxiv-cs-cl

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

Diagnosing and Repairing Factual Errors in RAG under Budget Constraints

arXiv:2606.29377v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) improves the factuality of large language models by grounding responses in external evidence, yet real-world deploy

local-aiarxiv-cs-ai

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

model-releasesarxiv-cs-cl

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

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