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Learning a Continuous Sepsis Severity Score Without Hour-by-Hour Supervision: A Two-Site Retrospective Study

arXiv:2608.27421v1 Announce Type: new Abstract: Currently used sepsis severity indices rely on fixed variables and weights established decades ago, which are coarsely discretized and calibrated to a c

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Learning-Augmented Online Allocation under Unreliable Advice: Robustness, Exposure Fairness, and Distribution Shift

DGX agent

arXiv:2608.26889v1 Announce Type: new Abstract: Learning-augmented algorithms improve online decisions using predictions, but unreliable advice may harm efficiency and fairness. We study an online all

safetyarxiv-cs-ai

28 Aug 2026

Learning the ARTS of Search for Automated Discovery

arXiv:2606.21891v2 Announce Type: replace Abstract: Scientific discovery can be formulated as an iterative search process over the space of hypotheses and experiments. Contemporary methods navigate th

Learning to Predict, Discover, and Reason in High-Dimensional Event Sequences

arXiv:2603.16313v3 Announce Type: replace Abstract: Electronic control units (ECUs) embedded within modern vehicles generate a large number of asynchronous events known as diagnostic trouble codes (DT

safetyarxiv-cs-ai

Learning to Reason with Curriculum I: Provable Benefits of Autocurriculum

arXiv:2603.18325v2 Announce Type: replace Abstract: Chain-of-thought reasoning, where language models expend additional computation by producing thinking tokens prior to final responses, has driven si

researcharxiv-cs-lg

Learning Transverse Momentum Distributions from Raw Scattering Events via Conditional Diffusion

arXiv:2608.27077v1 Announce Type: cross Abstract: Extracting transverse momentum dependent parton distribution functions (TMD PDFs) from semi-inclusive deep inelastic scattering (SIDIS) data is a cent

Learning Woody Clearing With Loss Alignment for Zero-Shot Regrowth and Woody Segmentation

arXiv:2608.26489v1 Announce Type: new Abstract: Detecting woody clearing is vital for managing biodiversity. Deep learning models can detect change in woody vegetation from bitemporal remote sensing i

safetyarxiv-cs-cv

Legal Rule Induction: Towards Generalizable Principle Discovery from Analogous Judicial Precedents

arXiv:2505.14104v2 Announce Type: replace Abstract: Legal rules encompass not only codified statutes but also implicit adjudicatory principles derived from precedents that contain discretionary norms,

Let Them Steal: Trapping Large Language Model Extraction Attacks with Knowledge Honeypot

arXiv:2606.15810v2 Announce Type: replace-cross Abstract: Large language models deployed as commercial APIs are vulnerable to model extraction attacks, while existing defenses either act too late or d

Letters hide the truth from our eyes: English homophones have meaningfully different phonetic realizations

arXiv:2608.26749v1 Announce Type: new Abstract: The distribution of spoken word duration of English homophones is known to co-vary with frequency of use. This study investigates whether other aspects

researcharxiv-cs-cl

Leveraging Large Language Models for Systematic Literature Review of Disease Spread Models

arXiv:2608.26150v1 Announce Type: new Abstract: Recent advancements in Large Language Models (LLMs) have created new opportunities to streamline and potentially automate many research processes, inclu

LeVJEPA: Efficient & Scalable Video Pretraining without the Heuristics

arXiv:2608.27395v1 Announce Type: cross Abstract: Video carries the temporal structure of the physical world, yet learning representations from it has remained computationally expensive: prevailing se

Linear Independence of Polynomial Compositions and Identifiability of Deep Neural Networks

model-releasesarxiv-cs-lg

arXiv:2608.27113v1 Announce Type: cross Abstract: Motivated by theoretical problems in deep learning, we conjecture that post-composing a fixed number of pairwise distinct nonconstant polynomials with

LiveSim: Simulating Environment-Shaped Users in Multi-Agent Live-Stream Ecosystems

arXiv:2608.26849v1 Announce Type: new Abstract: User behavior simulation with large language models~(LLMs) is increasingly used to support multi-agent ecosystem simulation. Existing simulators typical

LiveVVT: High-Fidelity Video Virtual Try-On in Real Time

arXiv:2608.26714v1 Announce Type: cross Abstract: Diffusion-based Video Virtual Try-On (VVT) achieves high visual fidelity through bidirectional spatio-temporal modeling, but complete-clip dependence

local-aiarxiv-cs-ai

LLaVAFlow: Preserving Latent Alignment Flow for Parameter-Efficient Multimodal Fine-Tuning

model-releasesarxiv-cs-cv

arXiv:2608.26820v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) exhibit strong generalization, visual instruction tuning for downstream tasks inevitably causes catastrop

LLM Agents for Time-Series: A Survey

arXiv:2608.26226v1 Announce Type: new Abstract: LLM-based agents are increasingly being developed for time-series problems, but their design choices vary substantially across task settings. This surve

LLM Analysis of 150+ years of German Parliamentary Debates on Migration Reveals Shift from Post-War Solidarity to Anti-Solidarity in the Last Decade

arXiv:2509.07274v4 Announce Type: replace Abstract: Migration has been a core topic in German political debate, from postwar expellee displacement to labor migration and recent refugee movements. Larg

LLM-Powered Swarms: A New Frontier or a Conceptual Stretch?

arXiv:2506.14496v3 Announce Type: replace Abstract: Swarm intelligence describes how simple, decentralized agents can collectively produce complex behaviors. Recently, the concept of swarming has been

LLMs Can Design Near-Optimal OR Algorithms

arXiv:2608.27296v1 Announce Type: new Abstract: We ask whether large language models (LLMs) can design effective algorithms for well-specified operations research (OR) problems. We study inventory con

LLMs for Academic Workflows: An Evaluation of Literature Reviews Generated with Short and Long Context Windows of LLMs

arXiv:2608.26145v1 Announce Type: new Abstract: Our research focuses on evaluating literature reviews generated in short and long context settings of large language models (LLMs) to investigate the im

LLMs in Digital EDA: A perspective on shifting roles from Generation to Orchestration

arXiv:2608.27184v1 Announce Type: cross Abstract: Electronic design automation (EDA) has advanced engineering productivity through successive generations of tooling that progressively automate synthes

LoRA as Oracle

arXiv:2601.11207v2 Announce Type: replace-cross Abstract: Practitioners increasingly deploy neural networks they did not train, and must audit them after the fact for hidden backdoors, without the tra

Applications

Lost in Compression: A Controlled Cross-Lingual Audit of Extractive Prompt Compressors

arXiv:2608.26175v1 Announce Type: cross Abstract: Extractive prompt compression promises to cut LLM inference costs by removing low-information tokens, and learned compressors such as LLMLingua-2 repo

applicationsarxiv-cs-ai

LowRankArena: A Standardized Evaluation Platform for SVD-Based LLM Compression

arXiv:2608.26389v1 Announce Type: new Abstract: SVD-based low-rank compression has become a fast-growing direction for reducing the memory and computational cost of large language models (LLMs). Howev

MACGen: Toward Functionally Correct and Secure Code Generation via Multi-Agent Collaboration

arXiv:2608.25457v2 Announce Type: replace-cross Abstract: Despite their strong ability to generate code, large language models often fail to produce secure code, as their outputs frequently contain se

Magnon-induced phononic Chern insulator

arXiv:2608.27011v1 Announce Type: cross Abstract: High-frequency artificial phononic crystals offer a low-loss platform compatible with on-chip integration, yet realizing Chern phononic phases at GHz

Applications

Magpie: Real-Time World Renderer for Interactive Games

arXiv:2608.27168v1 Announce Type: new Abstract: Modern game development relies heavily on conventional graphics pipelines. High-quality visual content requires modeling, material authoring, animation,

applicationsarxiv-cs-cv

Making Clinical Language Models Auditable: Concept-Guided Fine-Tuning for Robust Prediction

arXiv:2608.27397v1 Announce Type: cross Abstract: Clinical language models can achieve strong in-hospital accuracy yet fail under deployment shifts because they exploit note-specific artifacts (e.g.,

Making Latent Evolution Explicit: Operator-Structured Transitions for World Action Models

arXiv:2608.27259v1 Announce Type: new Abstract: World Action Models (WAMs) augment robot policies by predicting how task-relevant scene states may evolve under interaction. Recent WAMs increasingly pe

safetyarxiv-cs-lg

MAPLE: Metadata Conditioned LLM Pretraining for Locale-Aware Question Answering

arXiv:2601.15236v2 Announce Type: replace Abstract: Large language models can memorize competing locale-specific facts yet fail to select among them when the locale changes, defaulting instead to a si

Mapping Woody Vegetation from Multi-Source Imagery and Prediction Fusion for Enhanced Data Efficiency and Accuracy

arXiv:2608.26471v1 Announce Type: new Abstract: Tree cover maps are a fundamental remote sensing product, used to derive ecological insights about the landscape and are essential to change detection,

researcharxiv-cs-cv

Mapping Written Words to Spoken Words in a Different Language Using Only Visual Grounding

arXiv:2608.26925v1 Announce Type: new Abstract: In many low-resource settings, even just eliciting speech for data collection is difficult. One promising approach has been to ask speakers to describe

local-aiarxiv-cs-cl

Marine Autonomous Vehicle Fleet Scheduling to Maximise Scientific Impact

arXiv:2608.27271v1 Announce Type: cross Abstract: The marine science community increasingly relies on Marine Autonomous Vehicles (MAVs) to collect the critical environmental data required to understan

agentsarxiv-cs-ro

MCCE: A Framework for Multi-LLM Collaborative Search in Discrete Spaces with Similarity-Filtered Preference Learning

arXiv:2510.06270v2 Announce Type: replace-cross Abstract: Multi-objective discrete optimization problems, such as molecular design, pose significant challenges due to their vast and unstructured combi

local-aiarxiv-cs-ai

Mechanistic Reaction Prediction via Discrete Flow Matching on Graph-Structured Electron Occupation

arXiv:2608.27429v1 Announce Type: new Abstract: Chemical reactions are fundamentally transformations in electron space, yet most machine learning approaches model them either through extit{de novo} ge

MedFG-VQA: Low-Frequency Memory and Graph Attention for Lightweight Medical VQA

arXiv:2608.26848v1 Announce Type: cross Abstract: Medical Visual Question Answering (Med-VQA) holds significant promise for clinical decision support, yet faces challenges due to limited annotated dat

safetyarxiv-cs-ai

Memory Anchors for Continual Robot Learning

model-releasesarxiv-cs-ro

arXiv:2608.26545v1 Announce Type: new Abstract: Robot policies deployed in the wild should have the capability to continually learn new tasks without forgetting existing behaviors. A common approach t

MemToC: Benchmarking Memory-Tool Conflict Resolution in Large Language Models

arXiv:2608.26295v1 Announce Type: cross Abstract: Tool-augmented LLMs must arbitrate between two fallible sources when a tool return conflicts with their parametric memory, yet existing evaluations me

MENTOR: Reinforcement Learning via Flexible Teacher-Optimized Rewards for Tool-Use Distillation

arXiv:2510.18383v4 Announce Type: replace-cross Abstract: Distilling the tool-use capabilities of large language models (LLMs) into small language models (SLMs) is essential for their practical applic

safetyarxiv-cs-ai

MeshPriorDiT: Hierarchical Modeling for Action-Conditioned Cloth Dynamics

arXiv:2608.26766v1 Announce Type: new Abstract: Action-conditioned cloth dynamics prediction requires both locally plausible deformation and long-range coordination. Existing approaches largely follow

local-aiarxiv-cs-ro

Meta-Learning Where to Allocate Experts: Task-Conditioned Layer-Wise Compression for MoEs

arXiv:2608.26650v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models route each token to a subset of expert networks, increasing capacity while keeping per-token computation sparse. In many

Methodological and Conceptual Framework for 5D Multi-Table Analysis: A Unified Approach for Complex Data Reuse

arXiv:2608.26149v1 Announce Type: new Abstract: Multi-table learning remains a major challenge in machine learning for healthcare and other complex information systems. Relational data combine several

Mitigating Fabrication in Multi-Stage LLM Pipelines for Hiring: An Empirical Evaluation of Prompt Guardrails and Human-in-the-Loop Checkpoints

arXiv:2608.26171v1 Announce Type: cross Abstract: Multi-stage LLM hiring pipelines (resume improvement, interview question generation, answer feedback) can fabricate credentials, inflate qualifiers, a

safetyarxiv-cs-cl

Mitigating Strong-Modality Collapse in Multimodal Learning via Inverted Asymmetric Fusion

arXiv:2608.26879v1 Announce Type: new Abstract: Fusing multiple modalities is expected to improve model performance. However, on the MultiHuSE dataset, early, late, and symmetric attention fusion ofte

researcharxiv-cs-lg

MM-Spectrum: Multimodal Multi-spectral Molecular Structural Elucidation with a Stable MoE Framework

arXiv:2608.27286v1 Announce Type: new Abstract: Inferring molecular structures from multimodal spectroscopic measurements requires integrating complementary yet highly heterogeneous signals. However,

researcharxiv-cs-lg

Modality Maturity Index: A benchmark for assessing multimodal capabilities of omni models

arXiv:2608.26317v1 Announce Type: cross Abstract: Frontier language models are increasingly marketed as omni systems that can perceive and respond across modalities. Existing evaluation frameworks, ho

MODIS: Multi-Omics Data Integration for Small and unpaired datasets

arXiv:2503.18856v3 Announce Type: replace Abstract: An important objective in computational biology is the efficient integration of multi-omics data. The task of integration comes with challenges: mul

safetyarxiv-cs-lg