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Staleness-Learning Rate Scaling Laws for Asynchronous RLHF

arXiv:2607.01083v1 Announce Type: cross Abstract: High-throughput RLHF systems often decouple rollout generation from policy optimization, leading to the use of stale rollouts during learner updates.

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StateFlow: Dual-State Recurrent Modeling for Long-Horizon Time Series Forecasting

DGX agent

arXiv:2607.00197v1 Announce Type: new Abstract: Long-horizon multivariate time series forecasting (LTSF) remains challenging due to non-stationarity, regime shifts, and error accumulation. The Variabi

local-aiarxiv-cs-lg

2 Jul 2026

Stateful Token Reduction for Long-Video Hybrid VLMs

arXiv:2603.00198v2 Announce Type: replace-cross Abstract: Token reduction accelerates long-video vision--language models (VLMs), but existing methods target Transformers, where reduction is treated as

Statistical Properties of Training & Generalization

arXiv:2606.20299v2 Announce Type: replace-cross Abstract: Deep learning has managed to evade numerous intuitions from classical statistics to achieve unprecedented performance on a number of real-worl

applicationsarxiv-cs-lg

Steal the Patch Size: Adversarially Manipulate Vision-Language Models

arXiv:2607.00174v1 Announce Type: new Abstract: We present a black-box model-stealing attack that recovers private vision-tokenizer configurations of deployed vision-language models (VLMs), including

Stitched Embeddings: A Unified Latent Space for 3D Garments and 2D Patterns

arXiv:2607.00829v1 Announce Type: new Abstract: While garments are essential for realistic digital humans, their topological variety makes them much harder to model than parametric bodies. Traditional

applicationsarxiv-cs-cv

StochasT: Learning with Stochastic Turn Depth for Visual Instruction Tuning

model-releasesarxiv-cs-cl

arXiv:2607.00465v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) rely extensively on Visual Instruction Tuning (VIT) to elicit their multimodal reasoning capabilities. However, w

Stop Pretending Social Robots Are Inevitable

arXiv:2607.00142v1 Announce Type: new Abstract: This paper takes issue with the recent themes of both the RO-MAN and the HRI conferences for their portrayal of a future human-robot society as inevitab

researcharxiv-cs-ro

Structural Enforcement of Statistical Rigor in AI-Driven Discovery: A Functional Architecture

arXiv:2511.06701v3 Announce Type: replace-cross Abstract: AI-Scientist systems risk manufacturing spurious discoveries through uncontrolled multiple testing. We present a functional architecture that

applicationsarxiv-cs-ai

Structural Pattern Mining in Inka Khipus: Unsupervised Clustering, Provenance Classification, and a Computational Validation of the Santa Valley Match

arXiv:2607.00185v1 Announce Type: new Abstract: Khipus--knotted cord devices--were the primary recording medium of the Inka Empire (c. 1400-1532 CE), yet their system remains undeciphered. We present

researcharxiv-cs-cl

Structured 4D Latent Predictive Model for Robot Planning

arXiv:2607.01166v1 Announce Type: cross Abstract: Video predictive models are emerging as a powerful paradigm in robotics, offering a promising path toward task generalization, long-horizon planning,

applicationsarxiv-cs-cv

SuperFlex: Deformable Superquadrics for Point Cloud Decomposition

arXiv:2607.01015v1 Announce Type: new Abstract: Superquadrics have proven to provide a compact, geometrically meaningful representation for 3D objects. However, existing methods suffer from limited re

applicationsarxiv-cs-cv

Surfacing Variations to Calibrate Perceived Reliability of MLLM-generated Image Descriptions

arXiv:2507.15692v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) provide new opportunities for blind and low vision (BLV) people to access visual information in their daily l

safetyarxiv-cs-cl

Svarna: An Open Corpus Workbench for Modern Greek

model-releasesarxiv-cs-cl

arXiv:2607.00970v1 Announce Type: new Abstract: This paper introduces Svarna, a free, open-source, web-based corpus workbench for modern Greek. Svarna integrates five databases covering various regist

SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests

arXiv:2607.00990v1 Announce Type: cross Abstract: Large language model (LLM)-based software engineering agents are increasingly developed to resolve software issues by generating patches from issue re

Local Ai

SWE-Router: Routing in Multi-turn Agentic Software Engineering Tasks

arXiv:2607.00053v1 Announce Type: cross Abstract: Large language models (LLMs) embedded in multi-turn agentic harnesses are reshaping software engineering (SWE), but routing every task to a frontier m

local-aiarxiv-cs-ai

Synergistic Perception-Reasoning Governance: Grounding Medical MLLMs with Verifiable Anatomical Evidence

arXiv:2607.00060v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) show strong promise for clinical VQA and radiology report generation, yet inference-time hallucinations still u

researcharxiv-cs-cv

Tutorials

SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles

arXiv:2607.01105v1 Announce Type: new Abstract: We present SynLaD, a latent diffusion framework for small-molecule generation that unifies ligand-based drug design objectives (what to make) with synth

tutorialsarxiv-cs-lg

Tail-Shape Estimation in LLM Evaluation Is Fragile: A Protocol for Diagnosing False Positives

arXiv:2606.16511v2 Announce Type: replace Abstract: Recent work motivates moving large language model (LLM) evaluation from mean-based to tail-aware metrics, including conditional value-at-risk and ta

TallyTrain: Communication-Efficient Federated Distillation

arXiv:2607.00173v1 Announce Type: new Abstract: Federated learning is bandwidth-bound on two orthogonal axes: model size, which limits how often parameter-averaging methods can afford to merge, and cl

TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification

arXiv:2508.17519v3 Announce Type: replace-cross Abstract: Handling missing data in time series classification remains a significant challenge in various domains. Traditional methods often rely on impu

Task-Relevant Representation Decoupling for Visual Reinforcement Learning Generalization

arXiv:2607.00796v1 Announce Type: new Abstract: Visual Reinforcement Learning (VRL) has achieved considerable success in solving control tasks. However, generalizing learned policies to new environmen

researcharxiv-cs-lg

TCMA: Text-Conditioned Multi-granularity Alignment for Drone Cross-Modal Text-Video Retrieval

arXiv:2510.10180v2 Announce Type: replace Abstract: Unmanned aerial vehicles (UAVs) have become powerful platforms for real-time, high-resolution data collection, producing massive volumes of aerial v

Technical Report: Asynchronous Distributed Trajectory Estimation of Multi-Robot Systems

arXiv:2607.01106v1 Announce Type: new Abstract: Distributed trajectory estimation arises in many applications across robotics, but existing implementations typically do not consider asynchrony in agen

researcharxiv-cs-ro

TerraBench: Can Agents Reason Over Heterogeneous Earth-System Data?

arXiv:2606.13148v2 Announce Type: replace Abstract: Climate and environmental decision-making increasingly requires reasoning across heterogeneous inputs, including gridded physical data, satellite im

Testing Frontier Large Language Models' Physics Literacy in Parallel Physical Worlds

arXiv:2607.00276v1 Announce Type: cross Abstract: Current large-language-model (LLM) physics benchmarks are usually scored by answer accuracy, which cannot distinguish genuine reasoning from recall of

TetraSDF: Analytic Isosurface Extraction with Multi-resolution Tetrahedral Grid

arXiv:2511.16273v2 Announce Type: replace Abstract: Extracting an explicit surface that exactly matches the zero-level set of a neural signed distance function (SDF) remains challenging. Sampling-base

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The Binary Tree Mechanism is Optimal for Approximate Differentially Private Continual Counting

arXiv:2607.00876v1 Announce Type: cross Abstract: Private continual counting is a fundamental problem in differential privacy: given a binary stream of length n, where each 1 corresponds to the contri

researcharxiv-cs-lg

Tutorials

The Course of News Events: A Comparison of Bottom-Up and Top-Down Approaches for Collecting Text-Based Data about Disasters

arXiv:2607.00849v1 Announce Type: new Abstract: News articles are an important source of information on disaster impacts and adaptation. A key methodological challenge in socio-environmental studies i

tutorialsarxiv-cs-cl

The Illusion of High Utility in Safety Alignment of Text-to-Image Diffusion Models

arXiv:2607.00402v1 Announce Type: cross Abstract: Safety alignment of text-to-image (T2I) diffusion models aims to suppress harmful generations while preserving utility on benign prompts. Recent metho

safetyarxiv-cs-ai

The MMM Data Model -- A Normative Specification for Knowledge Interoperability in a Decentralisable Knowledge Commons

arXiv:2607.00032v1 Announce Type: new Abstract: Many information systems are built around documents: self-contained units optimised for print production and linear reading. While effective for large-s

applicationsarxiv-cs-ai

The Model Organism Lottery: Model Organism Interpretability Strongly Depends on Training Methodology

arXiv:2607.01033v1 Announce Type: new Abstract: Model organisms (MOs) - language models trained to exhibit undesired or unnatural behaviours - are frequently used as testbeds for evaluating white-box

The State-Prediction Separation Hypothesis

arXiv:2607.01218v1 Announce Type: cross Abstract: Transformers use the same forward computation stream to both predict the next token and store useful state for future token predictions. We formulate

Theoria: Rewrite-Acceptability Verification over Informal Reasoning States

arXiv:2607.01223v1 Announce Type: new Abstract: When should an AI system's answer be trusted? Formal proof assistants offer certainty but cannot reach most of the problem distribution; scalar LLM judg

Timesynth: A Temporal Fidelity Framework for Health Signal Digital Twins

arXiv:2607.00431v1 Announce Type: new Abstract: Forecasting models for health-signal digital twins must preserve the oscillatory, frequency, phase, and state-transition dynamics of physiological signa

TiRex-2: Generalizing TiRex to Multivariate Data and Streaming

arXiv:2607.01204v1 Announce Type: new Abstract: We introduce TiRex-2, a recurrent xLSTM-based time series foundation model that generalizes the univariate TiRex to multivariate forecasting with both p

applicationsarxiv-cs-lg

Topological Void Analysis A Mathematical Framework for Systematic Technical Innovation Discovery in Knowledge Spaces

arXiv:2607.00005v1 Announce Type: cross Abstract: Identifying where to innovate in a dense technical domain - such as operating systems or hardware/software co-design - is fundamentally a search probl

Toward Cybersecurity-Expert Small Language Models

arXiv:2510.14113v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are transforming everyday applications, yet deployment in cybersecurity lags due to a lack of high-quality, domai

Towards Accurate State Estimation: Motion Dynamics Kalman Filter for 3D Multi-Object Tracking

arXiv:2505.07254v2 Announce Type: replace Abstract: Precise 3D state estimation in multi-object tracking (MOT) is critical for self-driving cars, particularly for objects occluded. Motion modeling in

researcharxiv-cs-cv

Towards an automated AI-based framework for floor plan compliance checks for residential buildings

arXiv:2607.00015v1 Announce Type: cross Abstract: To improve residents' well-being in Australia's urban areas, governments have introduced policy reforms such as SEPP65, BADS, and SPP7.3 to enhance ap

safetyarxiv-cs-ai

Towards Developing a Multimodal Chat Assistant for University Stakeholders: RAG-based Approach

arXiv:2607.01115v1 Announce Type: cross Abstract: University stakeholders often face difficulties in accessing timely and reliable information, especially in developing countries, where there are very

Towards High-Resolution Visual Perception via Hierarchical Entity Exploration

arXiv:2607.00816v1 Announce Type: new Abstract: High-resolution (HR) image perception remains a key challenge in multimodal large language models (MLLMs), as fine-grained details are often lost when t

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Towards Memory-Efficient Autoregressive Video Generation via Instance-Specific Parametric Absorption

arXiv:2607.00712v1 Announce Type: new Abstract: Autoregressive (AR) streaming models have emerged as a powerful paradigm for long video generation. However, the linearly growing Key-Value (KV) cache p

local-aiarxiv-cs-cv

Towards Metric-Agnostic Trajectory Forecasting

arXiv:2607.01133v1 Announce Type: new Abstract: Accurate trajectory forecasting of surrounding traffic participants is a core capability for autonomous driving, enabling vehicles to anticipate behavio

Towards Robust Driving Perception: A Flexible Scale-Driven Family for Self-Supervised Monocular Depth Estimation

arXiv:2607.00736v1 Announce Type: new Abstract: Self-Supervised Monocular Depth Estimation (MDE) has garnered attention in recent years due to its independence from ground truth. However, most existin

researcharxiv-cs-cv

Towards Weaker Variance Assumptions for Stochastic Optimization

arXiv:2504.09951v2 Announce Type: replace-cross Abstract: We revisit a classical assumption for analyzing stochastic gradient algorithms where the squared norm of the stochastic subgradient (or the va

researcharxiv-cs-lg

TRACE: State-Aware Query Processing over Temporal Evidence Graphs for Conversational Data

arXiv:2607.00339v1 Announce Type: new Abstract: Conversational data is increasingly used as a persistent source of user state for long-running assistants and AI agents. However, querying this data rem

researcharxiv-cs-cl

Training-Free Debiasing of Diffusion Models via CLIP-Guided Denoising Optimization

arXiv:2607.00817v1 Announce Type: new Abstract: Text-to-image diffusion models achieve impressive visual quality, yet demographic bias remains a challenge, as neutral prompts consistently produce ster

safetyarxiv-cs-cv