Search: “benchmark”

Hybrid quantum recurrent neural network for remaining useful life prediction of turbofan engines

model-releasesarxiv-cs-lg

arXiv:2504.20823v3 Announce Type: replace Abstract: Accurate remaining useful life (RUL) estimation underpins safe operation and cost-effective maintenance of aerospace propulsion systems. We propose

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Model Releases

Interpretable Cross-Lingual Alignment in Small Language Models: Probing Cultural and Pragmatic Reasoning in Japanese-English Bilingual LLMs

DGX agent

arXiv:2608.14896v1 Announce Type: new Abstract: Large language models work well on English and behave in poorly understood ways on languages typologically far from it. Japanese is a clean example, whe

model-releasesarxiv-cs-cl

18 Aug 2026

LLMs Can Predict Failure Risk, But Struggle to Predict Which Collaboration Protocol Pays Off: Cost-Aware Protocol Routing Across Reasoning Tasks

arXiv:2608.14927v1 Announce Type: new Abstract: Multi-agent large language model (LLM) systems can improve reasoning by spending more computation, but deployment requires deciding when extra collabora

LongRCA Bench: Diagnosing Responsible Roles and Root Causes in Long-Horizon Agent Failures

arXiv:2608.15242v1 Announce Type: new Abstract: When a long-horizon agent execution fails, outcome-level evaluation reveals the unsuccessful result but not where the decisive error entered the traject

LORA-CRAFT: Cross-layer Rank Adaptation via Frozen Tucker Decomposition of Pre-trained Attention Weights

arXiv:2602.17510v2 Announce Type: replace-cross Abstract: We introduce LoRA-CRAFT (extbf{C}ross-layer extbf{R}ank extbf{A}daptation via extbf{F}rozen extbf{T}ucker), abbreviated CRAFT throughout, an e

Metaplasticity as adaptive gradient preconditioning for incremental learning

model-releasesarxiv-cs-lg

arXiv:2608.14634v1 Announce Type: new Abstract: Biological intelligence naturally prevents catastrophic forgetting through Complementary Learning Systems (CLS) theory, a macroscopic consolidation proc

MITE-Net: SWaP-Optimized 4K Video Tiny Target Perception for Embodied Edge SAR

arXiv:2608.15830v1 Announce Type: new Abstract: Real-time tiny target perception in high-resolution imagery is critical for embodied Search-and-Rescue (SAR) missions. However, strict Size, Weight, and

Applications

ML-AutoResearch: Training Machine Learning Research Agents with Automatically Generated Environments

arXiv:2603.17216v2 Announce Type: replace Abstract: With the advent of AI agents, automated scientific discovery is becoming an increasingly plausible goal. However, training agents to autonomously ex

applicationsarxiv-cs-ai

MME-VideoOCR: Evaluating OCR-Based Capabilities of Multimodal LLMs in Video Scenarios

arXiv:2505.21333v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved considerable accuracy in Optical Character Recognition (OCR) from static images. However, the

Navigation-Informed Embeddings: Dense-Retriever Adaptation from Agent Search Traces

arXiv:2608.15956v1 Announce Type: new Abstract: Agentic retrieval workflows produce query, retrieval, and stopping traces as a byproduct of answering questions. We study how these traces can adapt a d

Not All Attention Is Equal: A Quantitative Survey of the EEI Trade-off

arXiv:2608.15459v1 Announce Type: cross Abstract: Attention mechanisms have driven machine learning for a decade, from neural machine translation to language models that do general-purpose reasoning.

OvDSGG: End-to-End Open-Vocabulary Dynamic Scene Graph Generation

arXiv:2608.14835v1 Announce Type: new Abstract: Dynamic scene graphs (DSGs) capture spatio-temporal interactions across videos as langlesubject, predicate, objectrangle triplets, and underpin downstre

Palmyra x6 Technical Report: An Agentic, Tool-Use Model Post-Trained via Anchored Supervised Fine-Tuning

arXiv:2608.16620v1 Announce Type: cross Abstract: Palmyra x6 is a large language model optimized for use with enterprise-oriented agentic tasks. The model was built by post-training a Mixture-of-Exper

Picking the Right Image to Classify: Reliable-Input Selection in Teledermatology

arXiv:2608.16198v1 Announce Type: cross Abstract: Dermatology models face distribution shifts in teledermatology settings, where submitted images differ from the training data in lighting, angle, dist

pico-type: A 1.5M-Parameter Byte-Level Multi-Head Content Classifier

arXiv:2608.14658v1 Announce Type: cross Abstract: We introduce pico-type, a byte-level multi-head content classifier with approximately 1.5 million parameters that simultaneously predicts seven conten

PixRestore: Unified Image Restoration via Pixel Diffusion Transformer

arXiv:2608.16793v1 Announce Type: new Abstract: Unified image restoration (UIR) aims to recover high-quality (HQ) content from low-quality (LQ) images with different degradations using a single model.

SAGE-OR: Semi-supervised Adaptive Scene Graph Generation for Operating Rooms

arXiv:2608.15336v1 Announce Type: new Abstract: Current surgical scene graph generation methods depend on dense multi-modal supervision and specialized hardware (synchronized RGB-D sensors, calibratio

SAUL: Sharpness-Aware Augmented-Lagrangian Unlearning

model-releasesarxiv-cs-lg

arXiv:2608.16249v1 Announce Type: new Abstract: Machine unlearning in Large Language Models (LLMs) faces a critical trade-off between erasing target knowledge and preserving general utility. We propos

Research

T-LLM Compiler: Trusted LLM-based Code Optimization and Verification Framework

arXiv:2608.14953v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have opened opportunities to apply high-level code transformations to the field of code optimization, an

researcharxiv-cs-ai

The Machine's Internal Clock: Do LLMs Share Human Temporal Illusions?

model-releasesarxiv-cs-cl

arXiv:2608.15394v1 Announce Type: new Abstract: Human perception of time is subjective. Well-documented temporal illusions show that the brain relies on context and relational cues for judging duratio

TRACE: Trajectory Aware Reasoning for Multi-Turn Adversarial Conversation Evaluation

arXiv:2608.15594v1 Announce Type: new Abstract: Multi-turn jailbreak attacks have emerged as a critical safety threat to LLMs, as harmful objectives are decomposed across a sequence of apparently beni

Unsupervised Anomaly Detection for Image Dataset Quality Assurance in Multi-Center Breast MRI

arXiv:2608.16725v1 Announce Type: cross Abstract: Corrupted, inconsistent, or anomalous data silently threatens the safety and reliability of medical AI. Despite growing regulatory recognition of data

VibeWorlding: Can Multimodal Agents Construct 3D Open Worlds End-to-End?

arXiv:2608.15265v1 Announce Type: new Abstract: Constructing an interactive 3D open world from a user query is important. However, existing methods are primarily evaluated on idealized, simple queries

Safety

When Do Explanations Help In-Context Learning? A Comparative Study of Natural Language Explanation Types and Faithfulness

arXiv:2608.16627v1 Announce Type: cross Abstract: Natural language explanations (NLEs) are increasingly used as inputs, for example, as few-shot rationales that influence model behavior in in-context

safetyarxiv-cs-ai

Research

When Uncertainty Isn't Enough: An Empirical Study of Self-Correction in Code Generation

arXiv:2608.14659v1 Announce Type: new Abstract: Large language models for code generation often produce incorrect solutions without reliable indicators of failure. We study whether uncertainty estimat

researcharxiv-cs-ai

Agents

World-in-World: World Models in a Closed-Loop World

arXiv:2510.18135v2 Announce Type: replace Abstract: Generative world models (WMs) can now simulate worlds with striking visual realism, which naturally raises the question of whether they can endow em

agentsarxiv-cs-cv

Safety

AlignFace: Human-Aligned Face Similarity Metric with Interpretable Concept Relations

arXiv:2608.14130v1 Announce Type: cross Abstract: Computer vision models for generated facial content, such as face editing and privacy protection, increasingly affect people, requiring similarity met

safetyarxiv-cs-ai

CAST: Closed-form Analytic Semantic Transfer for Zero-Shot Classifier Extension

arXiv:2608.13751v1 Announce Type: new Abstract: Large pre-trained models have become foundational components of modern machine learning systems. Yet adapting these models to novel categories typically

Local Ai

E-S2Feat:Semantic-Guided Spiking Local Feature Detection and Description for Event Cameras

arXiv:2608.14027v1 Announce Type: new Abstract: Benefiting from high temporal resolution and dynamic range, event-based local feature methods have attracted increasing attention. However, event sparsi

local-aiarxiv-cs-cv

HERMES: a multi-agent framework for structured knowledge extraction from ultra-long documents in geoscience

model-releasesarxiv-cs-cl

arXiv:2608.14055v1 Announce Type: new Abstract: Authoritative scientific knowledge in geoscience remains largely trapped in legacy monographs and historical literature, where unstructured text and com

LightTeaNet: A Weakly Supervised Lightweight CNN for Multi-Label Tea Leaf Disease Detection and Localization

arXiv:2608.14178v1 Announce Type: new Abstract: Tea is known as an important crop in many parts of South and Southeast Asia, yet the production of tea is still hampered by the multiple diseases that d

LLM-Advisor: An LLM Advisor for Cost-efficient Path Planning across Multiple Terrains

arXiv:2503.01236v3 Announce Type: replace-cross Abstract: This paper addresses fixed-graph terrain-aware path refinement, in which a global planner is restricted to a predefined route space and may re

Tutorials

More Correct Mass, Worse Answers: Why Power Sampling Can Fail and How to Fix It

arXiv:2608.14420v1 Announce Type: new Abstract: Power Sampling sharpens a language model's distribution over complete generation trajectories, offering a verifier-free way to improve reasoning at infe

tutorialsarxiv-cs-lg

Tutorials

Reaction-Transformation-Aware Flow Matching for Generalizable Transition State Generation

arXiv:2608.14076v1 Announce Type: cross Abstract: Transition-state (TS) structures define the energetic barriers and mechanistic pathways of elementary chemical reactions, yet their identification rem

tutorialsarxiv-cs-ai

Simulation-Aware In-Context Policy Improvement for LLM-Aided Analog Layout Refinement

arXiv:2608.13767v1 Announce Type: new Abstract: Analog IC layout design remains a labor-intensive iterative process dominated by simulation-driven refinement. Although end-to-end layout generators acc

When Personal Memory Has No Single Answer: Evaluating LLM Agents under Irreducible Conflict

arXiv:2608.13921v1 Announce Type: new Abstract: LLM agents increasingly maintain personal memory across sessions, but it can conflict. Preferences depend on context, behavior evolves, and sources can

Wrong but Useful: Trajectory Value Beyond Answer Correctness in Multi-Agent Messages

arXiv:2608.14375v1 Announce Type: new Abstract: Multi-agent reasoning systems often use agreement, confidence, or automated scores to decide which messages should shape a final answer. Such filtering

Zero-Shot Skeleton-Based Action Anticipation

arXiv:2608.14243v1 Announce Type: new Abstract: Action anticipation (AA) aims to recognize ongoing human or humanoids actions from partial observations, enabling robots to predict intentions before th

A Generative Approach for Improving Multi-Label Defect Classification in Photovoltaic Modules

arXiv:2608.12725v1 Announce Type: new Abstract: This paper addresses the challenge of multi-label defect classification in electroluminescence (EL) images of photovoltaic (PV) cells. Training models o

Research

Are You Sure You're Sure? On the Impact of Instruction Tuning on Confidence and Lexical Diversity

arXiv:2608.13430v1 Announce Type: cross Abstract: Instruction-tuned language models achieve strong performance across a range of generation tasks, but have also recently been shown to exhibit verbaliz

researcharxiv-cs-ai

Can Vision-Language Models Assess Proxemic Risk from Egocentric Robot Images?

arXiv:2608.12515v1 Announce Type: new Abstract: Assessing proxemic danger from a robot's egocentric perspective is critical for safe embodied navigation in human environments and requires both visual

DFM Mimir v1: An Open HRM Delivering Frontier Performance at 1B Parameters Using Only Permissible Post-Training Data

arXiv:2608.13517v1 Announce Type: cross Abstract: Current large language model development relies on massive, often non-permissible datasets, creating a high barrier for researchers committed to open-

Do LLMs Beat Nash? Testing Decentralized Coordination in Self-Play Multi-Agent Games

model-releasesarxiv-cs-ro

arXiv:2608.12547v1 Announce Type: cross Abstract: Large language model agents deployed without a central controller are often assumed to require communication to coordinate their actions. We ask what

Local Ai

EgoCITE: Context-Augmented Indexing and Time-Aware Retrieval for Long-Horizon Egocentric Memory

arXiv:2608.12627v1 Announce Type: cross Abstract: Long-horizon egocentric memory transforms continuous first-person video and audio into a searchable record of past experiences. We demonstrate two bot

local-aiarxiv-cs-ai

EvDiff: Event-Based Video Reconstruction using One-Step Diffusion Models

arXiv:2511.17492v2 Announce Type: replace Abstract: As neuromorphic sensors, event cameras asynchronously record changes in brightness as streams of sparse events with the advantages of high temporal

FastThaiG2P: Lightning-fast Thai Grapheme-to-phoneme Conversion for Voice Agent Pipelines

model-releasesarxiv-cs-cl

arXiv:2608.12814v1 Announce Type: new Abstract: FastThaiG2P provides sub-millisecond Thai grapheme-to-phoneme conversion for text-to-speech pipelines (International Phonetic Alphabet and Kokoro-TTS co

FluctlightDB: A Memory Model of Data for AI Agents

arXiv:2608.12365v1 Announce Type: cross Abstract: For fifty years, data systems have answered two questions. The relational model asked which records match a predicate; the vector model asked which ve

Follow the Norm: Accounting for Fine-Tuning and Prompt Effects on Model Rationales

arXiv:2608.13250v1 Announce Type: cross Abstract: Normative datasets are often used to train and align AI systems, but the norms they contain can function as action-guiding patterns rather than neutra