Search: “model-releases”

Hierarchy-Aware Semantic Losses for Knowledge Graph Link Prediction

arXiv:2608.22981v1 Announce Type: new Abstract: Knowledge graphs are often accompanied by ontological class hierarchies that encode valuable semantic information, yet many link prediction methods eith

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Model Releases

HIRA: A Human-in-the-Loop Retrieval-Augmented Cascade for Document Classification in Regulated Industries

DGX agent

arXiv:2608.21792v1 Announce Type: new Abstract: Document classification in regulated industries is constrained by data residency, limited cold-start labels, scarce review capacity, and costly model-go

model-releasesarxiv-cs-ai

25 Aug 2026

HOT-POT: Optimal Transport for Sparse Stereo Matching

arXiv:2601.12423v2 Announce Type: replace Abstract: Stereo vision between images faces a range of challenges, including occlusions, motion, and camera distortions, across applications in autonomous dr

How Does Research Evolve? Tracing Cross-Domain Trajectories in NLP, ML, and CV Through Claim-Grounded Typed Citations

arXiv:2606.22342v2 Announce Type: replace Abstract: How does research evolve, and can we trace it at the level of individual claims? Scientific progress is not simply a uniform accumulation of facts.

How Merge-Tolerant Are Vision Transformers for Wheat Phenotyping?

arXiv:2608.23142v1 Announce Type: new Abstract: Vision-based wheat phenotyping requires repeated measurements under deployment constraints, from growth-stage recognition to wheat-head counting and org

How Much Regularization Survives Averaging? Update Masking in Federated Learning

arXiv:2608.23286v1 Announce Type: cross Abstract: Federated learning on non-IID data seeks flat minima to generalize across clients, and existing methods borrow sharpness-aware minimization from centr

How Useful are LLMs for Grammar Engineering? Cantonese ParGram Resources and Controlled Experimental Evaluation with English Baselines

arXiv:2608.23448v1 Announce Type: new Abstract: This paper presents new Cantonese ParGram resources and evaluates LLMs for knowledge-driven grammar engineering within a controlled experimental paradig

Improving O-RADS Risk Stratification from Ultrasound Reports: A Comparative Evaluation of Hybrid versus End-to-End LLM Reasoning Strategies

arXiv:2608.23061v1 Announce Type: new Abstract: Background: Automating clinical guideline-based decision-making with large language models (LLMs) remains challenging because of reliability, hallucinat

Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems

arXiv:2606.17443v2 Announce Type: replace Abstract: Large language models (LLMs) are becoming a major way for consumers to find products, but we do not yet understand how brands compete in this new ch

Industrial-Instruction: An End-to-End Framework for Building Instruction-Tuning and Benchmark Datasets from Industrial Technical Reports

arXiv:2608.22817v1 Announce Type: new Abstract: Industrial technical reports contain high-value knowledge for maintenance, troubleshooting, and product engineering, but their heterogeneous structure (

Inertial Manifold Neural Operator for Dissipative Time-Dependent Partial Differential Equations

arXiv:2608.23546v1 Announce Type: cross Abstract: In this paper, we introduce the Inertial Manifold Neural Operator (IMNO) for solving dissipative time-dependent partial differential equations (PDEs).

InstructMove: A Text-Indispensable Benchmark for Instruction-Following Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.22990v1 Announce Type: new Abstract: Vision-language-action (VLA) models have made general-purpose robot manipulation increasingly plausible by conditioning robot actions on natural-languag

IntentQA: Intent Question Answering in Videos by Cognitive Context Reasoning

arXiv:2608.23330v1 Announce Type: new Abstract: Video understanding requires intelligent agents to transcend mere recognition of visual facts and comprehend the underlying intents behind human actions

Interpretable AI with Local Distillation

arXiv:2608.23538v1 Announce Type: cross Abstract: Modern AI models such as tabular foundation models and gradient-boosted ensembles can outpredict classical methods, but provide little basis for reaso

iScheduler: Reinforcement Learning-Driven Continual Optimization for Large-Scale Resource Investment Problems

arXiv:2602.06064v2 Announce Type: replace-cross Abstract: Scheduling precedence-constrained tasks under shared renewable resources is critical to modern computing platforms. It is often modeled as the

K-Bench: measuring model performance on real scientific agent requests

arXiv:2608.21601v1 Announce Type: new Abstract: Benchmarks for scientific artificial intelligence are mostly written to be scored: multiple-choice questions, curated agent tasks with reference solutio

KAN-Robust-Bench: A Benchmark for Evaluating the Robustness of Kolmogorov-Arnold Networks

arXiv:2608.21488v1 Announce Type: cross Abstract: While machine learning models have demonstrated strong performance in many domains, these models have shown profound vulnerabilities when they are exp

KMGen: A Skill-based Approach for Synthetic Individual Patient Data Generation

arXiv:2608.22618v1 Announce Type: new Abstract: Individual patient data (IPD) from clinical trials is the substrate for survival modeling, meta-analysis, and safety research, yet IPD is rarely release

KVBoost: Chunk-Level Key-Value Cache Reuse with Deviation-Guided Recomputation for Efficient Large Language Model Inference

arXiv:2608.21362v1 Announce Type: new Abstract: Transformer-based large language models (LLMs) incur high prefill latency because key-value (KV) tensors must be recomputed for each request. Existing p

LaGEA: Language Guided Embodied Agents for Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2509.23155v3 Announce Type: replace Abstract: Robotic manipulation benefits from foundation models that describe goals, but today's agents still lack a principled way to learn from their own mis

Large-Small Model Collaboration for Zero-Shot Surgical Phase Recognition

arXiv:2608.22879v1 Announce Type: new Abstract: Task-specific lightweight models for surgical phase recognition excel at capturing temporal dynamics but generalize poorly under domain shift. Conversel

Learning to Look Again: Loss-Gap Supervision for Free-form Crop Routing in Vision-Language Models

arXiv:2608.21762v1 Announce Type: cross Abstract: Vision-language models (VLMs) fail many detail-centric questions for a concrete reason: the answer is visible in the image, yet lost after the image i

Length-Adaptive Decoding for Masked Diffusion Machine Translation

arXiv:2608.22274v1 Announce Type: cross Abstract: Machine translation tests masked diffusion language models (dLLMs) because every source token must be rendered faithfully, while fixed canvas decoding

Length-Controlled Margin-Based Preference Optimization without Reference Model

arXiv:2502.14643v3 Announce Type: replace Abstract: Direct Preference Optimization (DPO) is a widely adopted offline algorithm for preference-based reinforcement learning from human feedback (RLHF), d

Let Credit Follow Computation: Architecture-Aware Credit Transport for Large Language Model Reinforcement Learning

arXiv:2608.21501v1 Announce Type: new Abstract: Credit assignment in large-language-model reinforcement learning (LLM RL) can be separated into three objects: evidence about success, a transport opera

LetzCross: A Cross-Lingual Page-Level Benchmark for Multimodal Retrieval over Luxembourgish Documents

arXiv:2608.21714v1 Announce Type: new Abstract: Recent page-image retrievers such as ColPali have improved retrieval over visually rich documents, yet little is known about how they behave in cross-li

Lexical Coupling in GUI Element Grounding: Sentence Embeddings Track Labels across Mobile and Web

arXiv:2608.21794v1 Announce Type: cross Abstract: GUI grounding evaluations that expose UI elements as text metadata often treat high instruction-element embedding similarity as evidence of semantic g

LiST: Local-Simplex Test-Time LoRA Fusion

arXiv:2608.22370v1 Announce Type: new Abstract: Task-specific LoRA adapters offer a modular way to specialize large language and vision-language models. However, existing adapter composition methods a

LLM-based Agents for Forecasting and Prediction: Methods, Training, Evaluation, and Applications

arXiv:2608.23058v1 Announce Type: new Abstract: Large language models (LLMs) now support forecasting systems that combine language-based reasoning with temporal data, evidence retrieval, external tool

LLM-Specific Utility for Retrieval-Augmented Generation

arXiv:2510.11358v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) is typically optimized for topical relevance, yet its success ultimately depends on whether retrieved pas

LLM4LLM: Bridging Kernel Benchmarks and Real Deployment via Closed-Loop Agentic Optimization

arXiv:2608.21836v1 Announce Type: new Abstract: Large language models have become increasingly capable agents for low-level code and kernel optimization, but isolated kernel benchmarks provide only a

LLMs are Few-Shot Decision-Makers: Generalized Context-Aware Microgrid Frequency Control through Prompt Decision Transformer

arXiv:2608.21858v1 Announce Type: cross Abstract: The rapid evolution of energy structures has positioned microgrids as pivotal components of next-generation power systems, offering enhanced resilienc

LLMs for Survey Text Analysis - A Performance Comparison Between Humans and GPT-5 on Inductive Content Analysis

arXiv:2608.22417v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to support text analysis in qualitative research, yet evidence on their performance in inductive cont

Localization-Infused Vision-Language Semantic Fusion for Text-Guided Medical Image Segmentation

arXiv:2607.16327v2 Announce Type: replace Abstract: Medical image segmentation is essential for modern computer-aided medicine. Recently, text-guided segmentation has shown promise by incorporating cl

LongWoF-Bench: Evaluating EvoMap Genes for Verifiable Long-Workflow Tasks

arXiv:2608.23200v1 Announce Type: new Abstract: Large language models are increasingly expected to execute complex workflows whose success depends on maintaining interdependent constraints and produci

Loopy: Seamless Video Loop Generation via Anchored Looping Shift of Positional Embedding

arXiv:2608.23090v1 Announce Type: new Abstract: Looping videos are essential for practical applications such as web graphics, game development, and social media. However, existing approaches typically

Loss-Parameterized Fisher Width Along Learning Trajectories

arXiv:2608.21561v1 Announce Type: new Abstract: Fisher width measures the Gaussian width of a probe set after deformation by the local Fisher geometry. We study its evolution along learning trajectori

M^3ISR: A Multi-Modal Multi-View Benchmark for 3D/4D Gaussian Splatting and Feedforward Compression

arXiv:2608.22465v1 Announce Type: new Abstract: High-fidelity free-viewpoint video (FVV) and interactive rendering increasingly rely on explicit Gaussian representations, yet practical deployment rema

MADE: Benchmark Environments for Closed-Loop Materials Discovery

arXiv:2601.20996v2 Announce Type: replace Abstract: Existing benchmarks for computational materials discovery primarily evaluate static predictive tasks or isolated computational sub-tasks. While valu

Mamba-based Selective State Space Modeling Improves the Accuracy-Complexity Tradeoff of SmolVLA Vision-Language-Action Experts

arXiv:2608.21407v1 Announce Type: cross Abstract: Vision-language-action (VLA) models face a crucial tradeoff between their task success rate and the policy-call frequency. Executing a single action p

MASH-Bench: Diagnosing Cross-Source Failure in Mass-Shooting Risk Classification

arXiv:2608.22460v1 Announce Type: new Abstract: Public mass-shooting databases differ substantially in coverage, feature availability, and reporting practices, creating challenges for machine-learning

MDCPP: Multi-Robot Dynamic Coverage Path Planning for Workload Adaptation

model-releasesarxiv-cs-ro

arXiv:2509.23705v2 Announce Type: replace Abstract: Multi-robot coverage path planning commonly balances geometric area or path length under a constantspeed assumption. This assumption is inadequate w

Measuring Activation Control in Large Language Models

arXiv:2608.21664v1 Announce Type: new Abstract: Safe deployment of increasingly capable models will likely come to rely on latent-space monitoring as a complement to behavioral evaluations, especially

MediSkill-Evo: Process-Constrained Self-Evolution for Evidence-Grounded Clinical Interaction

arXiv:2608.23397v1 Announce Type: new Abstract: Interactive clinical agents must gather decisive evidence and convert it into grounded actions under partial observability. A correct final diagnosis al

MedReaMM: Evaluating Large Multimodal Models on Expert-Level Clinical Diagnostic Synthesis

arXiv:2608.22323v1 Announce Type: new Abstract: The application of Large Language Models (LLMs) to diagnostic decision-making has garnered growing interest. However, existing benchmarks largely focus

MemGuard: Persisting Verifier Signals for LLM-Agent Memory Governance

arXiv:2608.21867v1 Announce Type: new Abstract: LLM agents are moving from single-prompt use to long task streams in which reusable memory becomes a core capability for terminal, software-engineering,

MEMORY Wins All: Indirect Bias Injection Attacks via Social Media Feeds

arXiv:2608.22061v1 Announce Type: new Abstract: Personal AI agents routinely consume external content while performing tasks such as web browsing, email processing, and SNS feed summarization, and the

Meta-Ctrl: Guaranteed Plan Generation by Decoupling Syntactic and Semantic Constraints

arXiv:2608.22149v1 Announce Type: cross Abstract: LLMs generate fluent plans for robots but routinely violate the syntactic and se8mantic constraints they must satisfy to execute, and existing remedie