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Ravines in quantum cost landscapes: opportunities for improved VQA predictions

arXiv:2607.01329v1 Announce Type: cross Abstract: The geometric and topological structure of quantum cost landscapes (QCLs) governs the optimization and thus the predictive power of variational quantu

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Real-Time Visual Intelligence on Low-Cost UAVs: A Modular Approach for Tracking, Scanning, and Navigation

arXiv:2607.02298v1 Announce Type: new Abstract: Autonomous drones are rapidly transforming modern warfare and civil applications alike. This paper presents the development of an integrated intelligent

agentsarxiv-cs-ro

Reasoning effort, not tool access, buys first-try reliability in agentic code generation: an observational study

arXiv:2607.02436v1 Announce Type: cross Abstract: Agentic coding assistants are increasingly given extra capabilities, such as browser based testing tools and design oriented system prompts, on the as

local-aiarxiv-cs-ai

Reasoning LLM Improves Speaker Recognition in Long-form TV Dramas

arXiv:2607.02504v1 Announce Type: cross Abstract: Long-form TV dramas present a formidable challenge for comprehensive video understanding, where deciphering complex storyline often relies on extbf{sp

ReContext: Recursive Evidence Replay as LLM Harness for Long-Context Reasoning

arXiv:2607.02509v1 Announce Type: new Abstract: Understanding and reasoning over long contexts has become a key requirement for deploying large language models (LLMs) in realistic applications. Althou

Agents

Recorded an impromptu podcast episode with @swyx for @latentspacepod last month at @aiDotEngineer SG. Covered good ground including: - Why '…

Recorded an impromptu podcast episode with @swyx for @latentspacepod last month at @aiDotEngineer SG. Covered good ground including: - Why 'second brain' is the killer agent use case - Messaging platf

agentsswyx--x

Agents

Recursive Models for Long-Horizon Reasoning

arXiv:2603.02112v2 Announce Type: replace-cross Abstract: Modern language models reason within bounded context, an inherent constraint that poses a fundamental barrier to long-horizon reasoning. We id

agentsarxiv-cs-cl

RedCoder: Automated Multi-Turn Red Teaming for Code LLMs

arXiv:2507.22063v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) for code generation (i.e., Code LLMs) have demonstrated impressive capabilities in AI-assisted software developme

Applications

Reformalization of the Jordan Curve Theorem

arXiv:2607.01734v1 Announce Type: new Abstract: We present a case study in reformalization, a variant of autoformalization in which the input proof is not natural language but a formal development in

applicationsarxiv-cs-ai

Regularized Variational and Spectral Log-Density-Ratio Estimation in the Gaussian Location Model

arXiv:2607.01895v1 Announce Type: new Abstract: We study ridge-regularized log-density-ratio estimation in the Gaussian location model with a common covariance matrix. By affine invariance, the model

Repair the Amplifier, Not the Symptom: Stable World-Model Correction for Agent Rollouts

arXiv:2607.01767v1 Announce Type: new Abstract: As agent planning moves from short tool chains toward persistent workflows with thousands or tens of thousands of steps, failures will occur inside larg

local-aiarxiv-cs-ai

Restoring Linguistic Grounding in VLA Models via Train-Free Attention Recalibration

arXiv:2603.06001v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models enable robots to perform manipulation tasks directly from natural language instructions and are increasing

Rethinking Complexity Metrics for LLM-Integrated Applications: Beyond Source Code

arXiv:2607.01903v1 Announce Type: new Abstract: LLM-integrated applications blend natural language prompts with program code, and much of their runtime behavior originates in the prompt layer rather t

Rethinking Generic Object Tracking Toward Human-Level Perceptual Intelligence

arXiv:2607.01395v1 Announce Type: cross Abstract: At the heart of human visual perception lies the ability to maintain a continuous and coherent understanding of the external world. By integrating obs

local-aiarxiv-cs-ai

Rethinking Post-Hoc Calibration in Semantic Segmentation

arXiv:2607.01902v1 Announce Type: cross Abstract: Reliable confidence estimates are essential in semantic segmentation, especially in safety-critical settings where overconfident errors can mislead do

safetyarxiv-cs-lg

Rethinking Speech-LLM Integration for ASR: Effective Joint Speech-Text Training by Interleaving

arXiv:2607.01733v1 Announce Type: new Abstract: Speech-LLM integration has shown promising results by leveraging extensive textual pretraining, yet its specific benefits for automatic speech recogniti

Revisiting Chain-of-Thought Reasoning under Limited Supervision: Semi-supervised Chain-of-Thought Learning

arXiv:2607.01511v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning has emerged as an effective approach for activating latent reasoning capabilities in large language models. However, mo

Revisiting Decentralized Online Convex Optimization with Compressed Communication

arXiv:2607.01665v1 Announce Type: new Abstract: Decentralized online convex optimization (D-OCO) is a popular framework for distributed applications with streaming data. To tackle the communication bo

Risk Architecture for AI-Native Engineering Teams: An Organizational Framework for Agentic System Governance

arXiv:2607.01421v1 Announce Type: cross Abstract: Engineering management research has produced mature frameworks for software risk: ownership by feature, escalation by severity, and assurance by test

Robust and Explainable 3D Mode Shape Recognition Using Region-Aware Graph Neural Networks

arXiv:2607.01522v1 Announce Type: cross Abstract: Mode shape recognition is a fundamental task in automotive NVH development, yet it remains dependent on manual visual inspection by experienced engine

Robust for the Wrong Reasons: The Representational Geometry of LLM Robustness to Science Skepticism

arXiv:2607.01951v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly consulted on contested scientific questions, raising the concern that they will sycophantically retreat

Applications

Robust Image Processing Techniques for Construction Environment Monitoring Using Underwater Robots

arXiv:2607.01915v1 Announce Type: cross Abstract: This paper proposes a robust image processing framework for underwater robot-based construction environment monitoring, targeting complex degradations

applicationsarxiv-cs-ro

Rocket Report: Indian startup nears first launch; SpaceX's millenary milestone

model-releasesars-technica

India's first space unicorn is preparing for its first orbital launch , with Skyroot Aerospace developing the Vikram series of launch vehicles . In 2025, SpaceX posted a net loss of $4.9 billion , hig

Role-Aware Neural Convex Divergence Heads for Asymmetric Representation Learning

arXiv:2607.01762v1 Announce Type: new Abstract: Many representation learning problems involve directed relations, such as lexical entailment, sentence entailment, ontology hierarchy, and citation link

RuleChef: Grounding LLM Task Knowledge in Human-Editable Rules

arXiv:2607.01293v1 Announce Type: new Abstract: We present RuleChef, a framework that uses large language models (LLMs) to generate executable rules for NLP tasks such as text classification, Named En

RusFinChain: A Russian Benchmark for Verifiable Chain-of-Thought Reasoning in Finance with Fuzzy-Aligned Evaluation

model-releasesarxiv-cs-cl

arXiv:2607.01388v1 Announce Type: new Abstract: Multi-step symbolic reasoning is essential for robust financial analysis, yet most benchmarks neglect intermediate reasoning steps. FINCHAIN introduced

SA-HGNN: Sample-Adaptive Hyperbolic Graph Neural Network for EEG-Based Depression Recognition

arXiv:2607.02063v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) have been widely used to capture spatial functional connectivity patterns to improve electroencephalography (EEG)-based d

SAB-LVLM: Significance-Aware Binarization for Large Vision-Language Models

arXiv:2607.01876v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in multimodal understanding, yet their enormous parameter scale and cross-modal

SABER: A Semantic-Aligned Brain Network Analysis Framework via Multi-scale Hypergraphs

arXiv:2607.01901v1 Announce Type: cross Abstract: Effective brain disease diagnosis requires the synergy of brain connectivity patterns and high-level semantic knowledge. Existing methods, however, la

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model

arXiv:2607.01595v1 Announce Type: new Abstract: As the scale and complexity of cloud-based AI systems continue to escalate, ensuring service reliability through rapid fault detection and adaptive reco

Safeguarding LLM Agents from Misalignment through Provenance Analysis

arXiv:2607.01236v1 Announce Type: cross Abstract: As LLM agents gain increasing access to powerful tools, ensuring that their actions are aligned with the user's intent becomes critical. When an agent

Safety Targeted Embedding Exploit via Refinement

arXiv:2607.01859v1 Announce Type: new Abstract: Safety training for large language models (LLMs) is conducted predominantly in English, leaving uncertain how well safety mechanisms generalize to low-r

Safety Testing LLM Agents at Scale: From Risk Discovery to Evidence-Grounded Verification

arXiv:2607.01793v1 Announce Type: new Abstract: LLM agents increasingly perform autonomous actions through external tools, leading to complex and evolving safety risks. However, existing safety testin

Scalable and Distributed Silhouette Approximation

arXiv:2607.01993v1 Announce Type: cross Abstract: The silhouette is one of the most widely used measures to assess the quality of a k-clustering of a dataset of n elements. Its evaluation requires no

Scaling Latent Reasoning via Looped Language Models

arXiv:2510.25741v5 Announce Type: replace Abstract: Modern LLMs are trained to 'think' primarily via explicit text generation, such as chain-of-thought (CoT), which defers reasoning to post-training a

Tutorials

Scaling Laws for Grid-Based Approximate Nearest Neighbor Search in High Dimensions

arXiv:2607.01283v1 Announce Type: cross Abstract: Grid-based approaches to approximate nearest neighbor (ANN) search have been absent from modern scaling analyses. We present a systematic characteriza

tutorialsarxiv-cs-ai

Scaling to Multimodal and Multichannel Heart Sound Classification with Synthetic and Augmented Biosignals

arXiv:2509.11606v4 Announce Type: replace-cross Abstract: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for approximately 17.9 million deaths each year. Early det

Scaling Trends for Lie Detector Oversight in Preference Learning

arXiv:2607.01567v1 Announce Type: new Abstract: Deceptive behavior in LLMs is costly to monitor and prevent, motivating approaches such as Scalable Oversight via Lie Detectors (SOLiD) (Cundy & Gleave,

Scaling with Confidence: Calibrating Confidence of LLMs for Adaptive Test Time Scaling

arXiv:2607.01612v1 Announce Type: new Abstract: Training large language models (LLMs) with reinforcement learning (RL) has significantly advanced their performance on reasoning and question-answering

SCAPE: Accurate and Efficient LLM Training with Extreme Sparse Communication

model-releasesarxiv-cs-lg

arXiv:2607.01678v1 Announce Type: new Abstract: Communication increasingly dominates the cost of Large Language Model (LLM) pre-training, especially under data-parallel and sharded training schemes, w

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion

arXiv:2607.01777v1 Announce Type: cross Abstract: Radio frequency (RF) maps provide a compact representation of multipath propagation characteristics and are fundamental to channel modeling, coverage

Applications

SE(2) Navigation Mesh

arXiv:2607.01454v1 Announce Type: new Abstract: Global navigation for ground robots in complex multi-level environments requires representations that accurately capture traversable regions while enabl

applicationsarxiv-cs-ro

Tutorials

SelectTSL: Prompt-Guided Selective Target Sound Localization in Complex Scenarios

arXiv:2607.02343v1 Announce Type: cross Abstract: Humans can selectively attend to a target sound and estimate its direction in complex scenarios, whereas such selective localization remains challengi

tutorialsarxiv-cs-ai

Self-explainable Operator Learning for Discovering Spatial Patterns in Functional Data

arXiv:2607.02203v1 Announce Type: new Abstract: Operator learning has emerged as a powerful tool for modeling complex physical systems in functional spaces. However, their neural network-based archite

local-aiarxiv-cs-lg

Self-Gating Attention for Efficient Time Series Forecasting

arXiv:2607.02344v1 Announce Type: cross Abstract: Transformer architectures have shown strong potential in time series forecasting, where multi-head self-attention is widely used to capture temporal d

Self-Supervised Test-Time Tuning for Packet Loss Concealment

arXiv:2607.01823v1 Announce Type: cross Abstract: Packet loss concealment (PLC) reconstructs audio packets that are missing at the receiver, usually with a trained model whose parameters remain fixed

SemHash-LLM: A Multi-Granularity Semantic Hashing Framework for Document Deduplication

arXiv:2607.01601v1 Announce Type: new Abstract: Large scale document deduplication must preserve semantic equivalence while remaining efficient over massive corpora. We present SemHash LLM, a multi gr