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Spectral Embeddings of Degree-alpha Laplacians in Random Dot Product Graphs

arXiv:2608.10845v1 Announce Type: cross Abstract: Spectral clustering methods for network data are commonly based on a few matrix representations, such as the adjacency matrix and the symmetric Laplac

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SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information

DGX agent

arXiv:2608.10692v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across

model-releasesarxiv-cs-ai

12 Aug 2026

SPOTting the Future: Lookahead Explanations for Deep Reinforcement Learning

arXiv:2608.09967v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) agents achieve strong performance in complex environments, yet their decision-making processes remain difficult to int

SQuaT: Self-Supervised Knowledge Distillation via Student-Aware Quantized Teacher Features

arXiv:2608.10709v1 Announce Type: new Abstract: Quantization-Aware Training (QAT) enables the deployment of quantized models with minimal accuracy degradation. However, in practical scenarios, trainin

Static in Frames, Dynamic in Events: Rethinking Features in Event Cameras as Motion Cues

model-releasesarxiv-cs-cv

arXiv:2608.11075v1 Announce Type: new Abstract: Event cameras capture intensity changes asynchronously with high temporal resolution, requiring novel preprocessing methods for downstream tasks. Unlike

Status Association Does Not Reliably Predict Decision Leakage

arXiv:2608.10089v1 Announce Type: cross Abstract: Bias evaluations often move too quickly from evidence that a model encodes a social association to claims that the same association will alter consequ

Stay or Stray - A Dynamical Systems Viewpoint of Popularity Bias

arXiv:2608.10474v1 Announce Type: cross Abstract: Popularity bias in recommendation systems arises when a majority user class generates disproportionate interaction data, causing the system to increas

safetyarxiv-cs-lg

STCAD: Scalable Trajectory Clustering and Anomaly Detection on Terabyte-Scale AIS Data

arXiv:2608.10249v1 Announce Type: new Abstract: We present a scalable framework for unsupervised clustering of maritime trajectories derived from terabyte-scale Automatic Identification System (AIS) a

Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulation

arXiv:2608.10277v1 Announce Type: cross Abstract: We present a stochastic coupled emulator of E3SM version 3, built on the SamudrACE framework, which couples an atmosphere emulator (ACE2) with a full-

Stream Forcing: Constructing Unified Training Trajectory for Robust Streaming Video Generation

model-releasesarxiv-cs-cv

arXiv:2608.10439v1 Announce Type: new Abstract: Streaming video generation holds strong potential for world modeling, where future frames must be inferred online sequentially to form a continuous vide

StreamFlow: Dynamic Memory Flows for Streaming Video Understanding

arXiv:2608.10949v1 Announce Type: cross Abstract: Streaming video understanding requires multimodal large language models (MLLMs) to preserve relevant evidence from continuously evolving streams under

researcharxiv-cs-cl

Structural Guidance for Unified Joint Demosaicing and Denoising

arXiv:2608.09995v1 Announce Type: cross Abstract: Joint demosaicing and denoising is a fundamental step in camera image signal processing, yet remains challenging because different Bayer-like color fi

local-aiarxiv-cs-cv

SuperQuadricOcc: Real-Time Self-Supervised Semantic Occupancy Estimation with Superquadric Volume Rendering

arXiv:2511.17361v5 Announce Type: replace Abstract: Self-supervision for semantic occupancy estimation is appealing as it removes the labour-intensive manual annotation, thus allowing one to scale to

agentsarxiv-cs-cv

Surfacing the Unsaid: CUE-Bench for Affective Stance in Chinese Discourse

arXiv:2608.10810v1 Announce Type: cross Abstract: Emotion understanding in discourse requires reasoning beyond surface sentiment because speakers often convey affect through indirect, implicit, polite

Surgical WAM: A World-Action Model for Data-Efficient Surgical Robot Learning

arXiv:2608.11204v1 Announce Type: cross Abstract: Learning reliable surgical manipulation policies is bottlenecked by the scarcity of action-labeled demonstrations: teleoperated surgical robot (e.g.,

SynBoost: A Synergistic Framework for Fast Sampling of Diffusion Models

arXiv:2506.13058v2 Announce Type: replace-cross Abstract: Diffusion probabilistic models (DPMs) have demonstrated remarkable success in visual generation. However, their iterative sampling mechanism r

researcharxiv-cs-ai

TACTICL: Task-Aware Compression of Tabular ICL Models

arXiv:2608.10837v1 Announce Type: cross Abstract: The strong performance of foundation models for tabular tasks comes at substantial inference costs. Distilling models into task-specific architectures

TAF-MED: Multi-Turn Safety Refusal Collapse in LLMs Under Declared Self-Treatment Intent

arXiv:2608.10258v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly provide conversational health information that may influence treatment decisions, yet existing benchmarks do

TCAM for Autonomous Deformable Manipulation: The RMC2 Champion System for WBCD 2026 Track 4

arXiv:2608.10718v1 Announce Type: new Abstract: This technical report describes the RMC2 Team's champion solution for the WBCD 2026 Track 4: Deformable Manipulation Challenge. The task requires a robo

safetyarxiv-cs-ro

TEAMMix: Taxonomy Enrichment Augmentation and Minority-augmented Mixing Strategy for LLM-enhanced Weak-Supervised Hierarchical Text Classification

arXiv:2608.11044v1 Announce Type: new Abstract: Hierarchical Text Classification (HTC), as a critical text mining task, faces challenges such as complex label hierarchies and class imbalance. Existing

researcharxiv-cs-cl

TEASR: Training-Efficient Any-Step Diffusion Transformer for Real-World Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2606.16188v2 Announce Type: replace Abstract: Diffusion models excel in Real-World Image Super-Resolution (Real-ISR) due to their powerful generative priors but suffer from slow iterative sampli

TemMed-Bench: Evaluating Temporal Medical Image Reasoning in Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2509.25143v2 Announce Type: replace-cross Abstract: Existing medical reasoning benchmarks for vision-language models primarily focus on analyzing a patient's condition based on an image from a s

Templated or fully Synthetic? Prompt construction as a confound in measuring LLM political stance beyond writing assistance

arXiv:2608.11008v1 Announce Type: new Abstract: Political stance detection in LLMs has long been dominated by closed-ended, multiple-choice political survey questions---originally designed for humans,

safetyarxiv-cs-cl

Temporal Straightening for Latent Planning

arXiv:2603.12231v3 Announce Type: replace Abstract: Learning good representations is essential for latent planning with world models. While pretrained visual encoders produce strong semantic visual fe

local-aiarxiv-cs-lg

Temporally Grounded Compositional Camera Motion Understanding via Geometric Knowledge Distillation

arXiv:2608.10932v1 Announce Type: cross Abstract: Understanding camera motion is fundamental to video perception, with applications in spatial intelligence and controllable video generation. Multimoda

Test-Time Self-Evolving GUI Visual Grounding via Reflection-Guided On-Policy Self-Distillation

arXiv:2608.11191v1 Announce Type: cross Abstract: GUI Visual Grounding is a fundamental capability for GUI agents. Existing models typically freeze their parameters after deployment, limiting their ab

Tested Nemotron 3.5 Lightning locally on coding, Hermes Agent and agentic work

model-releasesr-localllama

Ran the model with quants (Q5) and MTP by bartowski with llama.cpp server. It takes ~24GB ram running on M5 Pro with 48GB at about 65t/s. On some tasks it was quite the overthinker. Overall, the quali

the @aiDotEngineer World Fair always one of the best events every year to talk to builders at the frontier of Research, Agents, Evals, Syste…

the @aiDotEngineer World Fair always one of the best events every year to talk to builders at the frontier of Research, Agents, Evals, Systems, etc A few weeks ago I gave a talk on - Continually Impro

agentsharrison-chase--x

The CASE Framework: A Multi-Disciplinary Control Architecture for Governing Enterprise Agentic AI

arXiv:2608.10153v1 Announce Type: new Abstract: Enterprises are deploying autonomous AI agents faster than they can govern them, and prevailing approaches stretch a single discipline, typically DevSec

The Deliberative Deficit: An Empirical Critique of LLMs in Democratic Discourse

arXiv:2608.10186v1 Announce Type: cross Abstract: LLMs are increasingly deployed in settings that require collective reasoning on complex, value-laden problems. Confidence in these deployments rests l

agentsarxiv-cs-ai

The Epistemic Politics of AI Anthropomorphism

arXiv:2608.00961v2 Announce Type: replace-cross Abstract: AI anthropomorphism is typically treated as a problem of user misperception requiring institutional correction. Users who engage in sustained

researcharxiv-cs-ai

The Evaluation Protocol Determines the Result: An Independent Reproduction of LeWorldModel on TwoRoom

model-releasesarxiv-cs-lg

arXiv:2608.10145v1 Announce Type: new Abstract: LeWorldModel trains a latent world model with a prediction loss and a single anti-collapse regulariser, and reports approximately 87% of goals reached o

The Gaussian-Multinoulli Restricted Boltzmann Machine: A Potts Model Extension of the GRBM

arXiv:2505.11635v2 Announce Type: cross Abstract: Many real-world tasks, from associative memory to symbolic reasoning, benefit from discrete, structured representations that standard continuous laten

Applications

The GenAI Catch-22: Use of Generative Artificial Intelligence in Norwegian Newsrooms During the 2025 Parliamentary Election

arXiv:2608.10773v1 Announce Type: cross Abstract: The increasing use of Generative Artificial Intelligence (GenAI) in journalism raises concerns about possible detrimental effects both on journalism a

applicationsarxiv-cs-ai

The GENEA Challenge 2026: A Large-Scale Disentangled Evaluation of Speech-Driven Gesture Generation on the Seamless Interaction Dataset

arXiv:2608.10839v1 Announce Type: new Abstract: This preprint presents the results of the fourth GENEA Challenge, a large-scale human evaluation of five speech-driven gesture-generation systems traine

safetyarxiv-cs-cv

The Hidden Puppet Master: Predicting Human Belief Change in Manipulative LLM Dialogues

arXiv:2603.20907v5 Announce Type: replace Abstract: As users increasingly turn to LLMs for practical and personal advice, they become vulnerable to subtle steering toward hidden incentives misaligned

safetyarxiv-cs-cl

The Illusion of Cross-Lingual Safety in Low-Resource Languages

arXiv:2608.11146v1 Announce Type: new Abstract: Safety alignment in large language models (LLMs) is largely developed in English, assuming these safeguards generalize across multilingual settings. How

local-aiarxiv-cs-cl

The Impact of Operational-Data Fidelity when Assessing Safety-Critical Autonomous-Vehicle Software

arXiv:2608.10025v1 Announce Type: new Abstract: For safety-critical software, data from the software's operational past (e.g. a sequence of success and failure events experienced by the software) can

safetyarxiv-cs-ro

The Kuramoto Neural Operator: Learning to Solve PDEs via Coupled Oscillator Dynamics

arXiv:2608.10234v1 Announce Type: cross Abstract: Operator learning is a rapidly advancing area of computational science. It is particularly well suited to problems where a partial differential equati

local-aiarxiv-cs-lg

The model punches above its weight, outperforming Gemma 4 E2B and Ministral 3 3B across a broad range of visual understanding benchmarks and…

The model punches above its weight, outperforming Gemma 4 E2B and Ministral 3 3B across a broad range of visual understanding benchmarks and delivers particularly strong results on document understand

model-releasescohere--x

The most dangerous document extraction failure isn't a wrong value. It's a missing row that looks like nothing is wrong. We released Extract…

model-releasesjerry-liu--x

The most dangerous document extraction failure isn't a wrong value. It's a missing row that looks like nothing is wrong. We released ExtractBench yesterday: 370 enterprise docs, 14 systems. The hardes

The Multilingual Quantization Tax: Structural Collapse and Typological Fragility in Edge SLMs

model-releasesarxiv-cs-cl

arXiv:2608.09941v1 Announce Type: new Abstract: While 4-bit weight quantization is critical for deploying Small Language Models (SLMs) on edge devices, evaluations of the resulting performance degrada

The Parser Already Knows: Lightweight Bias Correction in Constrained Decoding

arXiv:2608.10137v1 Announce Type: new Abstract: Grammar Constrained Decoding (GCD) forces Language Models (LMs) to produce syntactically valid outputs by masking out non-conforming tokens at each step

safetyarxiv-cs-cl

The Signal Rail: A Deterministic Motion Grammar for Communicating Conversational Agent State in Terminal Interfaces

arXiv:2608.10689v1 Announce Type: cross Abstract: Terminal interfaces to conversational agents report rich internal state (listening, thinking, executing tools, awaiting input, failing) almost entirel

agentsarxiv-cs-cl

The Truth Stays in the Family: Enhancing Contextual Grounding via Inherited Truthful Heads in Model Lineages

arXiv:2606.15821v2 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have produced many specialized multimodal LLMs (MLLMs) that share common foundational LLMs, fo

Industry

The web’s newest weapon against AI scrapers is a font

ShieldFont, created by designers Isaque Seneda and Gabriel Abrucio, uses ligature‑based word substitutions within a custom web font to render a perfectly readable page for human users while embedding

industryars-technica

ThinkAfford: Affordance-Centric Reasoning for Fine-Grained 3D Grounding in Cluttered Scenes

arXiv:2608.10981v1 Announce Type: new Abstract: Task-driven 3D affordance grounding aims to localize the functional region in a cluttered 3D scene that enables an action specified by a natural-languag

local-aiarxiv-cs-cv

Tutorials

ThinkRetrieve: Retrieval-Augmented Reasoning Traces for Test-Time Scaling

arXiv:2608.10928v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) improve performance by allocating additional inference-time compute to generate extended chain-of-thought reasoning. Howev

tutorialsarxiv-cs-ai