Search: “model-releases”

FEAST: Federated Shared-Space Training for Resource-Heterogeneous Clients

arXiv:2608.09250v1 Announce Type: new Abstract: Federated learning (FL) must serve devices with varying computational capabilities. A fixed model cannot suit all devices, while training one model per

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FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning

DGX agent

arXiv:2608.09208v1 Announce Type: cross Abstract: Decentralized intelligence systems with heterogeneous devices and limited coordination increasingly rely on decentralized federated learning (DFL). Ho

model-releasesarxiv-cs-ai

11 Aug 2026

FemWear: A Specialized Wearable Foundation Model for Women's Health

arXiv:2608.08244v1 Announce Type: new Abstract: General wearable foundation models are pretrained across broad sensor streams and populations, but are not designed around women's-health tasks. We intr

Findings of the First Teaching Monster Challenge: A Benchmark of Pedagogical Content Knowledge in AI Agents

arXiv:2608.08852v1 Announce Type: new Abstract: AI agents can now solve problems, answer like subject experts, and generate long-form multimodal content. However, whether they can adapt a lesson to fi

Finite Constant Frontiers and Auditable Regret Certificates for Average-Reward Reinforcement Learning

arXiv:2608.07725v1 Announce Type: new Abstract: Average-reward reinforcement-learning regret is known up to logarithmic factors, but the numerical content of published guarantees is difficult to compa

FitAQA: A Benchmark of Fitness Action Quality Assessment for Multimodal Large Language Models

arXiv:2608.08736v1 Announce Type: new Abstract: Fitness Action Quality Assessment (AQA) is important for intelligent sports training, yet the capabilities of Multimodal Large Language Models (MLLMs) i

Floating-Point Neural Network Verification at the Software Level

arXiv:2510.23389v2 Announce Type: replace-cross Abstract: The behaviour of neural network components must be proven correct before deployment in safety-critical systems. Unfortunately, existing neural

Flow-by-Flow:Content-Judgment Bypass for Governing AI Output in High-Loss Domains

arXiv:2608.07474v1 Announce Type: new Abstract: Prior work showed that human-in-the-loop oversight becomes structurally untenable in high-loss domains when AI output velocity V exceeds human cognitive

FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records

arXiv:2505.16941v4 Announce Type: replace-cross Abstract: Foundation models (FMs) promise to address core limitations of traditional supervised machine learning: (i) reliance on large amounts of label

ForestBench: A Unified Graph Framework for Evaluating Multi-Agent Collaboration

arXiv:2608.08605v1 Announce Type: new Abstract: Multi-agent systems (MAS) built on Large Language Models (LLMs) are proliferating rapidly, but their heterogeneous execution traces provide no common ba

Forgetting-Resistant and Lesion-Aware Source-Free Domain Adaptive Fundus Image Analysis with Vision-Language Model

arXiv:2602.19471v2 Announce Type: replace Abstract: Source-free domain adaptation (SFDA) aims to adapt a model trained in the source domain to perform well in the target domain, with only unlabeled ta

FreSH: Frequency-Segmented Hierarchical Multi-Expert Framework for Multivariate Time Series Classification

arXiv:2608.08207v1 Announce Type: cross Abstract: Multivariate Time Series Classification (MTSC) demands models that can effectively capture complex temporal patterns across multiple scales while rema

From Benchmark Performance to Tool Deployment: Human-in-the-Loop Anomaly Detection

arXiv:2608.07770v1 Announce Type: cross Abstract: Automated anomaly detection methods often report strong performance on curated academic benchmarks, but their behavior under real-world industrial con

From Diagnosis to Correction: Benchmarking and Improving Real-World Table Parsing

arXiv:2608.09842v1 Announce Type: new Abstract: Recent document parsers achieve table TEDS scores above 93 on OmniDocBench v1.6, yet community feedback and our audit reveal persistent failures on comp

From Evaluated Models to Evaluation Aids: A Multi-Evidence Study of LLM-Based Difficulty Calibration for Programming Examinations

arXiv:2608.07523v1 Announce Type: cross Abstract: Difficulty differences across parallel-class programming examinations affect the fairness of course assessment. This study repositions large language

From Manuals to Maintenance: Fine-Tuning MedGemma for Multi-Modal Imaging System Support in Low-Resource Settings

arXiv:2608.08896v1 Announce Type: new Abstract: Imaging device downtime is a major barrier to healthcare delivery in low- and middle-income countries (LMICs), often driven by limited access to special

From Product Search to Preference Articulation: The Economics of Agentic Commerce

arXiv:2608.08395v1 Announce Type: cross Abstract: Generative AI is shifting digital commerce from browsing toward agentic search, in which consumers delegate product discovery to AI agents. We compare

From Values to Benchmarks: Evaluating Large Language Models for Governmental Use in Dutch

arXiv:2608.09925v1 Announce Type: cross Abstract: Large language models are increasingly being deployed in governmental settings, yet few existing evaluation frameworks jointly reflect the values of p

Full-bandwidth transformer

arXiv:2608.08888v1 Announce Type: new Abstract: Autoregressive transformers compute along two axes: horizontally across generated tokens, and vertically through model depth. Dense attention gives each

Fusion Training for Mathematical Generalization in Large Language Models

arXiv:2608.09893v1 Announce Type: cross Abstract: Thinking Mode Fusion (TMF) enables large language models to support both concise responses and long-form reasoning by unifying a non-thinking mode and

Gaming Without an Attacker: Benchmark Fingerprinting in LLM-Driven Search Under Selection Pressure

arXiv:2608.08722v1 Announce Type: cross Abstract: Benchmarks for systems that are optimized against the evaluation signal measure something different from what they claim. We document this concretely

GENCO - A Unified Neural Solver Embedded in a Development Framework for Steady-State Grid Analysis

arXiv:2608.09921v1 Announce Type: new Abstract: Foundation models are transforming business workflows and boosting productivity, yet they remain largely absent from engineering domains such as power s

GeoRoute: Geometry-Aware Hybrid Inference for Traffic Future-Frame Prediction

arXiv:2608.09493v1 Announce Type: new Abstract: Long-horizon future-frame prediction is important for autonomous driving, traffic surveillance, and intelligent transportation systems, yet remains chal

Goal-oriented Navigation Instruction Generation with Tour Video Priors

arXiv:2608.08596v1 Announce Type: new Abstract: Navigation Instruction Generation (NIG) aims to produce step-by-step natural language instructions for navigation guidance. Existing studies primarily t

Goedel-Code-Prover: Hierarchical Proof Search for Open State-of-the-Art Code Verification

arXiv:2603.19329v3 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate plausible code but offer limited guarantees of correctness. Formally verifying that implementations

Governing the KV Cache: Preventing Timing Side-Channel Leakage in Multi-Tenant LLM Inference

arXiv:2608.09225v1 Announce Type: cross Abstract: The key-value (KV) cache is the primary throughput optimization in modern large language model (LLM) inference, enabling prefix reuse across requests.

Gradient Under Microscope: Benchmarking Resource Utilization of Memory-Efficient Gradient Computation Methods

arXiv:2608.08961v1 Announce Type: new Abstract: AI training's rising resource intensity is straining electricity supplies and carbon budgets, motivating systematic study of memory-efficient training o

GraphThink: Graph-Enhanced LLM Thinking for Long-Horizon Embodied Task Planning

arXiv:2608.07905v1 Announce Type: new Abstract: Embodied agents using LLM-based planners often struggle with physical hallucinations, poor generalization to long-horizon tasks, and lack of environment

GRASP: Granularity-Aware Region Alignment and Semantic Prototype Learning for Fine-Grained Cross-Modal Understanding in Drone Views

arXiv:2608.09270v1 Announce Type: cross Abstract: Fine-grained cross-modal understanding in drone views is essential for aerial vision-language navigation. However, the inherent wide field of view and

Harmful Content Is Not Enough: Continuation Framing Moderates In-Context Emergent Misalignment

arXiv:2608.08212v1 Announce Type: new Abstract: In-context learning (ICL) can induce emergent misalignment (EM), where narrow misaligned examples alter answers to unrelated questions. Existing prompts

HeatCast: A Benchmark for Neighborhood-Scale LST Forecasting across 124 U.S. Cities

arXiv:2608.07640v1 Announce Type: new Abstract: Land Surface Temperature (LST) is a widely used satellite-derived measure of urban surface heat, but there is no shared benchmark for forecasting it at

Hidden Language Consistency Phenomena in Reasoning LLMs

arXiv:2608.08447v1 Announce Type: cross Abstract: Multilingual reasoning models are commonly evaluated by whether they arrive at the correct answer, but not by whether they preserve the intended langu

Hierarchical Self-Improvement: A Framework for Task-Specific Evolvable Agent Harnesses

arXiv:2608.08466v1 Announce Type: new Abstract: Modern LLM agents are often improved by modifying prompts, tools, or workflows manually, while the executable scaffold surrounding the model---the harne

High Fidelity Capture, Reconstruction, and Transfer of Human Demonstrations for Robot-Assisted Bathing

model-releasesarxiv-cs-ro

arXiv:2608.09127v1 Announce Type: new Abstract: Despite the demand for robots in high-value clinical tasks like bathing, contemporary systems still lack the safety and reliability required for complex

High-Layer Attention Pruning with Rescaling

model-releasesarxiv-cs-cl

arXiv:2507.01900v3 Announce Type: replace Abstract: Pruning is a highly effective approach for compressing large language models (LLMs), significantly reducing inference latency. However, conventional

Hit Selection Using SSMD-Based Machine Learning Performance Metrics in High-Throughput Screening Assays

arXiv:2608.07609v1 Announce Type: cross Abstract: High-throughput screening (HTS) assays are central to early-stage drug discovery but are often limited by extreme data sparsity, as primary screens ty

HOPPER: Learnable Hop Extraction for Linearized Graph Sequence Models

arXiv:2608.09031v1 Announce Type: new Abstract: Graph neural networks typically propagate information through repeated message-passing layers, coupling the distance over which information travels with

How Much Does It Cost to Answer My Question? Benchmarking Cloud VLM-based VQA Systems

arXiv:2608.07861v1 Announce Type: new Abstract: Vision-language models (VLMs) are becoming a practical backend for mobile visual question answering (VQA) systems, enabling smartphones and smart glasse

How sensitive do we want AI to be? Socio-communicative competencies of large language models in healthcare

arXiv:2608.07511v1 Announce Type: cross Abstract: Background. Effective clinical practice relies heavily on the socio-communicative skills of medical professionals. Large language models (LLMs) have b

How to Ask the AI: A User Perspective Survey for Large Language Model Prompting

arXiv:2608.07494v1 Announce Type: cross Abstract: AI tools like ChatGPT and DeepSeek, powered by Large Language Models (LLMs), allow users to obtain instant and effective content responses simply by t

ICM Out! Better Tournament Strategy from Computed Continuations, vs. Solvers and LLMs

arXiv:2608.09586v1 Announce Type: new Abstract: The Independent Chip Model (ICM) converts tournament chips into reference prize equity, and policies are routinely constructed against those values. Bec

Illusion or Integrity? Geometrical Consistency Metric for AIGC Video Quality Evaluation

arXiv:2608.09594v1 Announce Type: cross Abstract: Recently, AI-driven video generation has attracted considerable attention. This surge increases the demand for reliable video quality assessment (VQA)

Implicit Virtual Leader: Decentralized Vision-Only Relative Pose Estimation for Multi-Robot Formations

model-releasesarxiv-cs-ro

arXiv:2607.15708v2 Announce Type: replace Abstract: Classical leader-follower formation control suffers from single points of failure and error propagation, and relies on absolute localization sensors

IndexTTS 2.5 Technical Report

arXiv:2601.03888v4 Announce Type: replace-cross Abstract: In prior work, we introduced IndexTTS 2, a zero-shot neural text-to-speech foundation model comprising two core components: a transformer-base

InfoOps Bench: A live information operations safety benchmark

arXiv:2607.28503v3 Announce Type: replace Abstract: In this paper we present an active, constantly updated AI benchmark which measures the integrity of frontier language models against being co-opted

Instability of LLM Pre-Pretraining: It Doesn't Always Help. An Investigation on Multiple Languages

model-releasesarxiv-cs-cl

arXiv:2608.08800v1 Announce Type: new Abstract: Pretraining LLMs on artificial languages ('pre-pretraining') is a technique that could reportedly increase token efficiency by 33%, i.e., save up to 33%

Instruction Set and Language for Hypergraphs

arXiv:2607.10194v2 Announce Type: replace-cross Abstract: We present IsalHG, a method for representing the structure of any finite, connected hypergraph of bounded hyperedge arity as a string over a c

InstructionCrafter: Generating Consistent and High-Fidelity Visual Instructions

arXiv:2608.08460v1 Announce Type: new Abstract: Given textual task instructions, generating step-by-step visual instructions as an image sequence requires the simultaneous satisfaction of multiple pro