Search: “benchmark”

PICasso: An AI-Enabled Design Framework for Autonomous Optimization of Silicon Photonic Devices

arXiv:2608.26113v1 Announce Type: new Abstract: We present PICasso, an AI-assisted framework for automated synthesis, verification, and optimization of photonic integrated circuits (PICs) from natural

28 Aug 2026

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Real-time Unsupervised Object Discovery from Asynchronous Event Streams

DGX agent

arXiv:2608.26644v1 Announce Type: new Abstract: Event cameras capture pixel-level intensity changes with microsecond resolution to produce highly sparse asynchronous data streams. For visual perceptio

model-releasesarxiv-cs-cv

28 Aug 2026

Refusal Is Not Robustness: Auditing Confident Fabrication in Large Language Models on a Provably Uninformative Clinical Pain Speech Transcript

arXiv:2608.26167v1 Announce Type: new Abstract: Hallucination and abstention benchmarks rarely establish that a model could not have known the correct answer, making it difficult to distinguish approp

28 Aug 2026

A General-Purpose Framework for Chemical Reaction Representation with Atomic Correspondence and Flexible Condition Adaptation

arXiv:2411.17629v3 Announce Type: replace Abstract: Motivation: Organic synthesis is fundamental to the chemical industry, particularly in domains such as pharmaceutical development. While artificial

Can You Trust Frozen Hematology Foundation Models under Acquisition Shift?

arXiv:2608.25148v1 Announce Type: new Abstract: Frozen hematology foundation-model (FM) embeddings reach near-saturated in-domain white-blood-cell (WBC) accuracy, but clinical deployment demands relia

From Specialization to Generalization: Instruction-tuned LLMs for Robust Harmful Content Mitigation

arXiv:2608.25605v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate impressive performance across a wide range of general NLP tasks; however, their effectiveness in sensitive doma

IDEAlign: Comparing Ideas of Large Language Models to Domain Expert

arXiv:2509.02855v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to produce open-ended, interpretive annotations, yet there is no validated, scalable measure of i

Learning Continuous Regional Temperature Fields with Lead-Time and Resolution Queries

arXiv:2608.25823v1 Announce Type: new Abstract: Accurate regional near-surface temperature forecasting is fundamental to short-range weather services and downstream risk assessment. Existing deep lear

Model-Agnostic Open-Set Air-to-Air Visual Object Detection for Reliable UAV Perception

arXiv:2509.09297v2 Announce Type: replace Abstract: Open-set detection is crucial for robust UAV autonomy in air-to-air object detection under real-world conditions. Traditional closed-set detectors d

PA-CoT: Profile-Adaptive Chain-of-Thought for Personalized Nutritional Consulting

arXiv:2608.24907v1 Announce Type: cross Abstract: In health and nutrition consulting, widely used prompting methods pass the user profile as an unstructured block without a dedicated analysis step, le

Padamitra: Grounded Glossary Generation for Classical Sanskrit

arXiv:2608.25038v1 Announce Type: new Abstract: We introduce grounded glossary generation, a structured task requiring models to recover semantically meaningful Sanskrit phrases and produce translatio

StreamPI: Streaming Multimodal Temporal Modeling for Vision-Language-Action Models

arXiv:2608.26067v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated effectiveness in robot manipulation, yet state-of-the-art models such as pi0.5 operate under a sin

The Von-Neumann State-Space Transformer for neural decoding

arXiv:2608.25088v1 Announce Type: new Abstract: Cortical computation is strikingly low-dimensional: a handful of latent variables, carried in a neural population's activity, steer the higher-dimension

When RAG Fails to Equalize: Geo-bias in Factual Question Answering over Public Companies

arXiv:2608.25717v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is widely assumed to mitigate factual errors in large language models (LLMs), but it remains unclear whether retrie

A Geometric Theory of Robust Fairness Audits

arXiv:2608.24818v1 Announce Type: new Abstract: Neighborhood-based fairness audits evaluate individual fairness by comparing predictions among similar individuals in feature space. Despite their wides

ACE: A Self-Correcting Agentic Canvas Editor for Multi-Slide Presentation Automation

arXiv:2608.24103v1 Announce Type: new Abstract: Commercial design platforms increasingly edit documents through large language model (LLM) agents, but two practical problems block reliable deployment:

Research

Diverse by Reasoning: Harnessing the Wisdom of LLM Crowds for Future Prediction

arXiv:2608.24001v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for future prediction, motivating the use of multiple models as a wisdom-of-the-crowd mechanism. Howe

researcharxiv-cs-ai

Agents

EgoErrorVQA: Assess Egocentric Comprehension Capabilities through Procedural Errors for Ego-Agentic AI

arXiv:2608.24134v1 Announce Type: new Abstract: The majority of our everyday activities are procedural and consist of sequences of interdependent steps. However, existing benchmarks for Visual Agents

agentsarxiv-cs-cv

LG-GER: Language-Guided Group Emotion Recognition via Multimodal Evidence Distillation

arXiv:2608.23880v1 Announce Type: new Abstract: Inferring the collective emotional state of a group of people from a single image, a task known as group emotion recognition (GER), requires integrating

Meta^n: Recursive Self-Improvement through Emergent Depth

arXiv:2608.24735v1 Announce Type: new Abstract: Self-improving LLM agents refine answers, not the process that produces those answers. Systems that add a meta-level hold that level fixed, and those th

MolEmb: Multimodal Large Language Models Can Be Strong Molecular Embedding Models

arXiv:2608.23646v1 Announce Type: new Abstract: Molecular embedding models can serve as foundational infrastructure for computational chemistry and drug discovery, where reusable vector representation

MoRF-AST: Calibrated Probabilistic Virtual Sensing for Structural Monitoring under Changing Operating Conditions

arXiv:2608.24531v1 Announce Type: cross Abstract: Probabilistic full-field reconstruction provides uncertainty-aware response evidence for structural reliability assessment, yet inference from sparse

Safety

NeuralParker: A Reinforcement Learning Planner for Irregular Parking Environments

arXiv:2608.24485v1 Announce Type: cross Abstract: Automated parking commonly assumes marked slots and short approach maneuvers. Delivery and service vehicles, however, may need to reach an operator-sp

safetyarxiv-cs-lg

Neurosymbolic Alignment for Physiologically-Safe Clinical Language Models

arXiv:2608.24534v1 Announce Type: new Abstract: Clinical LLMs can generate recommendations that are factually plausible yet physiologically unsafe. We investigate whether safety alignment can be impro

PhysicsBench: A Unified Leaderboard for Generative and Predictive Models in Engineering Design and Simulation

arXiv:2608.24056v1 Announce Type: new Abstract: Generative and predictive artificial intelligence models are increasingly used to generate geometry and to predict physical fields and scalar quantities

Recursive Agentic Reasoning

arXiv:2608.23956v1 Announce Type: new Abstract: Test-time reasoning methods such as iterative refinement, decomposition, and repeated sampling are often evaluated in isolation, making their gains diff

Restoring Without Forgetting: Continual Learning Across Image Degradations

arXiv:2608.23799v1 Announce Type: cross Abstract: Recent progress in image restoration has converged on all-in-one architectures that jointly handle multiple degradations within a single network. Thes

Robust Motion Generation using Part-level Reliable Data from Videos

arXiv:2512.12703v2 Announce Type: replace-cross Abstract: Extracting human motion from large-scale web videos offers a scalable solution to the data scarcity issue in character animation. However, som

Safety

RoG-DAgger: Rollout-Guided Post-Training for End-to-End Driving

arXiv:2608.24525v1 Announce Type: new Abstract: Recent end-to-end driving systems demonstrate strong performance on closed-loop benchmarks, yet are still predominantly trained on fixed expert-collecte

safetyarxiv-cs-ro

SAGE: From Direct Answering to Evidence-Grounded Inference for Chinese Ancient Document Understanding

arXiv:2608.24011v1 Announce Type: cross Abstract: Chinese ancient document understanding demands complex visual, linguistic, and historical reasoning. Current Large Vision-Language Models (LVLMs) typi

Hardware

Scalable Question-Centric Text-to-Image Evaluation: Reliable Ranking, Fine-Grained Diagnosis, and Cost-Aware Routing

arXiv:2608.24112v1 Announce Type: new Abstract: Modern text-to-image (T2I) models often have similar total scores but different strengths, making practical selection difficult. Fine-grained benchmarks

hardwarearxiv-cs-ai

SIREN-Bench: Behavior-Driven Generation and Evaluation of Emergency-Vehicle Interactions

model-releasesarxiv-cs-ro

arXiv:2608.24094v1 Announce Type: new Abstract: Emergency vehicles (EMVs) can reorganize surrounding traffic as civilian vehicles brake, change lanes, or form rescue corridors in response to their pas

Taming foundation model with invariance-oriented pre-training for broad-spectrum EEG analysis across signal-level, brain-state, and brain-health tasks

arXiv:2608.24597v1 Announce Type: cross Abstract: Electroencephalography (EEG) is a widely used window into human brain function, but most EEG models remain tied to a one-dataset-one-model supervised

Applications

Wontopos Tablet 2: Measuring Multilingual and Multimodal Memory Retrieval Without Lexical Matching

arXiv:2608.23920v1 Announce Type: cross Abstract: We measure tablet-2, a production long-term memory engine for language models, on the text benchmarks the field already uses and on cross-lingual retr

applicationsarxiv-cs-cv

A Physical Response-and-Memory Model for Muon Optimization

arXiv:2608.22994v1 Announce Type: cross Abstract: Training large language models is costly. How low a loss the same compute can ultimately reach depends on how each step's gradient is converted into a

Research

All four leading LLMs talk more than they listen to personality-verified synthetic help-seekers

arXiv:2608.22425v1 Announce Type: cross Abstract: Large language models are increasingly consulted at moments of distress, yet single-turn benchmarks neither test sustained exchanges nor distinguish b

researcharxiv-cs-cl

Beyond the Harness: End-to-End Optimization of Context Artifacts for Enterprise Text-to-SQL

arXiv:2608.22830v1 Announce Type: new Abstract: Deploying LLMs for enterprise Text-to-SQL is bottlenecked less by the model than by what context reaches it: business logic spans thousands of tables, a

CHIMERA Challenge: Biochemical Recurrence Prediction in Prostate Cancer Patients using multimodal datasets

arXiv:2608.21497v1 Announce Type: cross Abstract: Biochemical recurrence (BCR), defined as any detectable prostate-specific antigen level after prostatectomy with confirmatory elevation, is widely use

Safety

Evaluation Awareness in Language Models: Representation, Verbalization, and Control

arXiv:2608.21766v1 Announce Type: cross Abstract: Both capability and safety benchmarks rest upon the assumption that the behavior of language models undergoing a test is informative about their behav

safetyarxiv-cs-ai

Gauss--Hermite Quadrature for Gaussian-Mixture Entropy with an Action-Space Hermite Surrogate

arXiv:2608.21467v1 Announce Type: cross Abstract: Gaussian distributions are used to model uncertainty in signals and states, and Gaussian mixtures are often used when the underlying distribution is m

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

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

Applications

Loss Landscape Features That Make Adam Stall: Definitions, Estimators, and the Preconditioned Hessian View

arXiv:2608.22145v1 Announce Type: new Abstract: Across implicit-neural-representation (INR) architectures and analytic benchmarks we observe that a thoroughly tuned Adam (especially its learning rate

applicationsarxiv-cs-lg

Retrieval Needs Multivectors: An Exponential Separation

arXiv:2608.21494v1 Announce Type: cross Abstract: Recent works have highlighted the expressive limitations of embedding based retrieval models through both theoretical analyses and challenging benchma

Building and Evaluating a Synthetic Bengali Speech Resource for Telecom Customer Care

arXiv:2608.20346v1 Announce Type: new Abstract: Speech systems used in customer-facing applications often require domain-specific language coverage. We present a synthetic Bengali speech dataset for t

ClawSentry: A Progressive Multi-Tier Security Monitor for Safeguarding Autonomous LLM Agents

arXiv:2608.21101v1 Announce Type: cross Abstract: As large language model (LLM) agents move from conversation to executing code, reading local files, and orchestrating external tools, a single agent h

Designing a Robust LLM-Based Evaluation System for Agentic AI in Drug Discovery Through Human Alignment

arXiv:2608.21057v1 Announce Type: new Abstract: Agentic large language model (LLM) systems are reshaping scientific workflows in chemistry and drug discovery, but evaluating their open-ended, tool-aug

Evaluating Large Language Model Performance on International Maritime Dangerous Goods Code Compliance

arXiv:2608.21036v1 Announce Type: new Abstract: The transport of dangerous goods by sea is a high-consequence activity governed by the International Maritime Dangerous Goods (IMDG) Code, a complex reg