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SuperCoder: Assembly Program Superoptimization with Large Language Models

arXiv:2505.11480v4 Announce Type: replace-cross Abstract: Superoptimization is the task of transforming a program into a faster one, and ideally the very fastest possible one, while preserving its inp

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SuperLocalMemory 4.0: The Governed Memory Operating System for AI Agents

DGX agent

arXiv:2608.08253v1 Announce Type: new Abstract: AI agents are becoming shared infrastructure, yet durable memory is commonly assembled from separate retrieval, governance, and operational components.

model-releasesarxiv-cs-ai

11 Aug 2026

SuperNeuroMAT: An Efficient Matrix-based Simulator for Spiking Neural Networks

arXiv:2608.08479v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) offer a promising pathway to energy-efficient AI and brain-inspired computing. However, their widespread adoption is hi

Support Selection Beyond Smooth DAG Exactness: Completion Geometry,Score Margins, and Selective Certificates

arXiv:2608.08103v1 Announce Type: new Abstract: Smooth acyclicity constraints answer whether a weighted support is a DAG, whereas structure learning asks which support change should be made. Existing

researcharxiv-cs-lg

SurakshaEval: An Indic Safety Benchmark for Multilingual LLMs

arXiv:2608.07862v1 Announce Type: new Abstract: Existing safety evaluation datasets for large language models (LLMs) predominantly focus on English and Western contexts, often overlooking the linguist

Agents

SurgLAT: Surgical Latent Attention Tracking for Depth-Aware Robotic Laparoscope Control

arXiv:2608.07876v1 Announce Type: new Abstract: Autonomous laparoscopic camera control requires continuous understanding of the surgeon's operative intent in dynamic surgical scenes, where the target

agentsarxiv-cs-ai

SurgWMBench: A Vision-Based Benchmark for World-Modeling Surgical Instrument Motion Planning

model-releasesarxiv-cs-ro

arXiv:2608.08070v1 Announce Type: new Abstract: Reliable surgical planning requires models that move beyond recognizing the current surgical step or imitating expert demonstrations, and instead antici

SurveyReview: A Reviewer-Aligned Benchmark for Survey Evaluators

arXiv:2608.07641v1 Announce Type: new Abstract: The rapid advancement of large language models has transformed survey writing from a months-long manual effort into an automated process. As generation

SWE-Bench ProMax: Benchmarking Agents on Large-Scale Multilingual Code Refactoring

arXiv:2608.09802v1 Announce Type: new Abstract: As AI coding agents take on increasingly complex, long-horizon software engineering tasks, existing benchmarks are rapidly saturating and their evaluati

Hardware

SwiftQK: Fast and Communication-Efficient Tensor Parallelism for Query-Key Normalization

arXiv:2608.09160v1 Announce Type: new Abstract: Query-Key Normalization (QK-Norm) improves the training stability and quality of modern Large Language Models (LLMs). However, under Tensor Parallelism

hardwarearxiv-cs-lg

SwissCrop25: A National Multi-Year Benchmark for Operational Crop Mapping

model-releasesarxiv-cs-cv

arXiv:2608.09497v1 Announce Type: new Abstract: Operational crop mapping requires models that generalise across years, resolve fine-grained crop taxonomies, and distinguish cropland from surrounding l

Safety

Symbolic Attack Chain Generation from Atomic Red Team Techniques: An Empirical Study of Predicate Representation Granularity

arXiv:2608.00143v2 Announce Type: replace-cross Abstract: Automated attack chain generation is critical for modern cybersecurity, yet manual construction fails to scale as adversary behaviors expand.

safetyarxiv-cs-ai

SymboUQ: Symbolic Uncertainty Quantification for Spatial Reasoning in LLMs

arXiv:2608.00417v2 Announce Type: replace Abstract: Although large language models (LLMs) can produce fluent spatial reasoning traces, their intermediate relations may fail to support the final conclu

SymDiag: Explainable Diagnosis for LLM Reasoning via Neuro-Symbolic Verification

arXiv:2608.08786v1 Announce Type: new Abstract: Large language models (LLMs) increasingly serve as data-driven reasoners, yet their chains-of-thought (CoT) can be unfaithful even when final answers ar

local-aiarxiv-cs-ai

Safety

SynVAR: Synergizing Spatial and Semantic Alignment in Visual Autoregressive Model

arXiv:2608.07948v1 Announce Type: new Abstract: VAR has gained widespread popularity due to its next-scale prediction paradigm. However, it faces substantial performance bottlenecks when handling comp

safetyarxiv-cs-cv

Tabular Numeric Stretch Transformation

arXiv:2608.09162v1 Announce Type: cross Abstract: Tabular data presents unique challenges for deep learning due to its heterogeneous nature, where numeric features exhibit diverse distributions, scale

TAMS: Task-Aware Multi-View Adaptive Streaming for Wireless Telerobotic Manipulation

arXiv:2608.09731v1 Announce Type: new Abstract: Wireless telerobotic manipulation relies on timely multi-view video feedback, but the available uplink bandwidth is often limited and dynamic. This pape

researcharxiv-cs-ro

Targeted Counterfactual Fingerprinting for Black-Box LLM Ownership Verification

arXiv:2608.08195v1 Announce Type: cross Abstract: Large language models (LLMs) are high-value assets that can be derived through redeployment, fine-tuning, quantization, or further alignment. Because

local-aiarxiv-cs-ai

Targeted Label-Flipping and Oversampling Attacks on Federated Conditional GANs

arXiv:2608.09314v1 Announce Type: new Abstract: In a federated learning setup for GANs, several adversarial attacks are possible. One such attack is label flipping, in which malicious clients delibera

local-aiarxiv-cs-lg

Task-Adaptive 3D Cross-Field MRI Translation via Field-Conditioned Content-Style Pretraining

arXiv:2608.09264v1 Announce Type: new Abstract: Magnetic field strength is a major source of domain shift in magnetic resonance imaging (MRI), affecting signal-to-noise ratio, tissue contrast, spatial

researcharxiv-cs-cv

Task-Oriented Formation Decision via Reinforcement Learning: Herding an Attacking Swarm

model-releasesarxiv-cs-ro

arXiv:2608.09258v1 Announce Type: new Abstract: Multi-robot systems can accomplish tasks that are difficult for a single robot by organizing into task-specific formations. Different from existing stud

Task-to-Model Optimization for Enterprise LLM Coding Assistants: A Data-Driven Framework for Cost-Optimal Routing

model-releasesarxiv-cs-lg

arXiv:2608.08528v1 Announce Type: new Abstract: Enterprise AI coding assistants incur substantial inference spend, and naive token-cost minimization often fails to reduce end-to-end cost once retries,

TCS-BENCH: Benchmarking State-of-the-Art Generative AI Theoretical Computer Science Research Ability

arXiv:2608.09538v1 Announce Type: cross Abstract: We introduce TCS-Bench, a benchmark for evaluating Large Language Models (LLMs) on research-level Theoretical Computer Science (TCS) proof generation.

Applications

TDMA Based Communications Control Co-Design for Cooperative Carrying: Delay Calibration and Sampling-Rate Optimization

arXiv:2608.09556v1 Announce Type: new Abstract: Multi robot teams performing cooperative transportation face a fundamental challenge: maintaining stable control while keeping communications efficient.

applicationsarxiv-cs-ro

TeaMatch: Teachable Cross-Modal Representation Learning for 2D-3D Matching

arXiv:2608.09590v1 Announce Type: new Abstract: Learning reliable correspondences between images and point clouds is fundamental for 2D-3D matching. Despite recent progress in detection-free methods,

researcharxiv-cs-cv

TelemetrySuffBench: Is Agent Telemetry Sufficient for Failure-Origin Diagnosis?

arXiv:2608.07899v1 Announce Type: new Abstract: Agent systems increasingly expose execution traces, yet telemetry that reveals a failure may still be inadequate for identifying where that failure orig

TEMPER: Tensorized Efficient Manifold-constrained Parameterization for Expressive Residual Routing

arXiv:2608.07851v1 Announce Type: cross Abstract: Residual connections rely on a static residual pathway, and are essential for training deep neural networks. Hyper-connections (HC) increase the expre

Temporal Generalization in fNIRS-Based Autism Classification: A Cross-Time-Window Transfer Benchmark

arXiv:2608.07567v1 Announce Type: cross Abstract: Functional near-infrared spectroscopy (fNIRS) is a promising modality for autism spectrum disorder (ASD) classification, yet existing approaches assum

Temporal Misgrounding in Legal RAG: A Versioned-Corpus Benchmark for French Tax Law

arXiv:2608.09393v1 Announce Type: cross Abstract: We identify and quantify temporal misgrounding: the systematic retrieval and citation of the currently in-force version of a legal article when the ap

Temporal Sepsis Modeling: a Relational and Explainable-by-Design Framework

arXiv:2601.21747v4 Announce Type: replace-cross Abstract: Sepsis remains one of the most complex and heterogeneous syndromes in intensive care. While deep learning models achieve competitive performan

Test-Time Augmentation for LLMs: When Input Diversity Beats Output Diversity at Matched Compute

arXiv:2608.09351v1 Announce Type: cross Abstract: Test-time scaling improves LLM accuracy but multiplies inference cost, making the accuracy gained per unit of compute the metric that matters in deplo

Test-time Generalization for Physics through Neural Operator Splitting

model-releasesarxiv-cs-lg

arXiv:2602.00884v2 Announce Type: replace Abstract: Neural operators have shown promise in learning solution maps of partial differential equations (PDEs), but they often struggle to generalize when t

Test-Time Prototype Adaptation for Open-Vocabulary Semantic Segmentation

model-releasesarxiv-cs-cv

arXiv:2608.08290v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) repurposes a pretrained CLIP encoder for dense prediction without additional labeled supervision. Existing

Test-Time Scaling for CAD Generation via Verifier-Free Consensus Selection

arXiv:2608.09706v1 Announce Type: cross Abstract: Large language models can write parametric CAD programs from a natural-language description (text-to-CAD generation), but a single sample is often wro

researcharxiv-cs-lg

Testing Hypotheses from the Social Approval Theory of Online Hate: An Analysis of 110 Million Messages from Parler

arXiv:2507.10810v3 Announce Type: replace Abstract: We examined how social approval motivates online hate via the social approval theory, which argues social approval signals on hate messages predict

researcharxiv-cs-cl

Tether-Inertial Localization for Planetary Drones

arXiv:2608.09515v1 Announce Type: new Abstract: Recent developments in planetary exploration have shown the potential of Unmanned Aerial Vehicles (UAVs), such as the Ingenuity helicopter that provided

local-aiarxiv-cs-ro

Tevatron-Elastic: A Unified Abstraction for Training Elastic Retrievers and Rerankers

arXiv:2608.08809v1 Announce Type: new Abstract: A single model scale challenges the flexibility of a production retrieval system: some settings need it faster, others need a smaller index, and the rig

TeXFix-Bench: An Empirically Grounded Multi-Format Benchmark for LLM-Based Document Source Repair

arXiv:2608.07617v1 Announce Type: new Abstract: Scientific and technical writing depends on markup sources that must compile: LaTeX, Typst, and Markdown pipelines fail on missing delimiters, mismatche

TGIF: Text-Guided Layer Fusion Mitigates Hallucination in Multimodal LLMs

arXiv:2601.03100v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) typically rely on a single late-layer feature from a frozen vision encoder, leaving the encoder's ric

Safety

The Anatomy of a Prompt Injection: A Component Model for Structured Analysis

arXiv:2608.07808v1 Announce Type: cross Abstract: Four years after prompt injection was first identified in 2022, attacks are still predominantly documented as verbatim strings rather than structured

safetyarxiv-cs-ai

The Announcement Carries the Cue: Markup, Boundaries, and the Notation of Pre-Training Corpora

arXiv:2608.09093v1 Announce Type: cross Abstract: How a document's arrangement is written down, its notation, is a training variable that no dataset card records. The field has established that text-e

The Authority Expectancy Effect in Multi-User Conflict

arXiv:2608.08026v1 Announce Type: new Abstract: We investigate how social authority (SA) signals interact with severity-based prioritization in large language models, operationalizing each axis as a m

Agents

The Belief-Desire-Intention Ontology for modelling mental reality and agency

arXiv:2511.17162v2 Announce Type: replace Abstract: The Belief-Desire-Intention (BDI) model is a cornerstone for representing rational agency in artificial intelligence and cognitive sciences. Yet, it

agentsarxiv-cs-ai

Agents

The Capability Ladder: A Curriculum-Modernization Framework for Workforce Readiness in the AI Era

arXiv:2608.07779v1 Announce Type: new Abstract: Artificial intelligence is changing the task composition of computing work faster than curricula and training typically adapt. This is a curriculum-fram

agentsarxiv-cs-ai

The Cell Must Go On: Agar.io for Continual Reinforcement Learning

arXiv:2505.18347v3 Announce Type: replace-cross Abstract: Continual reinforcement learning (RL) concerns agents that are expected to learn continually, rather than converge to a policy that is then fi

The Collaboration Gap: Exploration and Benchmarking of Open-World Agentic Cooperation

arXiv:2511.02687v2 Announce Type: replace Abstract: The trajectory of AI development suggests that we will increasingly rely on agent-based systems powered by language models, composed of independentl

The Cost of Adaptivity: Matching Lower Bounds Across Learning Problems

model-releasesarxiv-cs-lg

arXiv:2608.08826v1 Announce Type: new Abstract: Adaptive procedures must work without nuisance information an oracle may use, such as a gradient scale or smoothness index, and robust procedures may ha

The Evolution of Mixture-of-Experts Architectures in Large Language Models: Routing, Topology, Load Balancing, and Expert Parallelism

arXiv:2608.08650v1 Announce Type: new Abstract: Mixture-of-Experts models increase parameter capacity while keeping the computation activated by each token bounded, but their architectural evolution c