Search: “models”

TangramPuzzle: Evaluating Multimodal Large Language Models with Compositional Spatial Reasoning

arXiv:2601.16520v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in visual recognition and semantic understanding, yet precise compo

26 Aug 2026

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Safety

BehaviorWorldGen: Closing the Loop between Action Models and World Simulators via Controllable Behavior-Aware Structured World Generation

DGX agent

arXiv:2608.22187v1 Announce Type: cross Abstract: Modern driving action models are increasingly improved in a self-improvement loop, where a learned world simulator imagines future observations and th

safetyarxiv-cs-cv

25 Aug 2026

Beyond Factual Knowledge: Benchmarking and Learning Step-Level Procedural Rule Reasoning in Large Language Models

arXiv:2608.22753v1 Announce Type: new Abstract: Large language models (LLMs) excel at text understanding and generation, yet still struggle to reliably understand and apply externally provided procedu

CallScreenBench: Benchmarking Small Language Models as Phone Secretaries

arXiv:2608.01033v2 Announce Type: replace-cross Abstract: Language models small enough to run on a handset, quantized to a few bits, are increasingly capable of acting on their user's behalf -- which

Claim-Level Confidence Calibration for Reliable Decision Making with Large Language Models

arXiv:2608.22483v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly support decision-making in high-stakes domains, but they often hallucinate and express confidence that is misa

Agents

Counterfactual Quotient Models: Learning What Actions Change, Not What the World Does

arXiv:2608.22092v1 Announce Type: new Abstract: Reinforcement-learning models commonly predict complete future states, observations, or feature occupancies, even though action selection depends only o

agentsarxiv-cs-lg

Credal Large Language Models for Semantic Commitment under Uncertainty

arXiv:2608.23244v1 Announce Type: cross Abstract: Large language models (LLMs) often produce fluent but incorrect answers with unwarranted confidence. A central limitation is that standard LLMs repres

DIME: Query-Efficient Framework for Membership Inference on Diffusion Models

arXiv:2608.22824v1 Announce Type: new Abstract: Membership inference attacks expose whether individual records were used to train a model, yet existing attacks on diffusion models are largely heuristi

Do Large Language Models Perform Well on Comprehending Poetic Logic in Modern Chinese Poetry?

arXiv:2608.21827v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved significant progress across a wide range of natural language processing (NLP) tasks, yet their ability to und

FrugalSOT - Frugal Search Over the Models

arXiv:2608.21621v1 Announce Type: new Abstract: In on-device NLP tasks, limited resources of embedded hardware, such as the Raspberry Pi 5, require efficient inference strategies. This paper introduce

Tutorials

Learning Mamba as a Continual Learner: Meta-Learning Selective State Space Models for Continual Learning

arXiv:2412.00776v5 Announce Type: replace Abstract: Continual learning (CL) learns from a non-stationary data stream without storing or re-training on all seen samples. Meta-continual learning (MCL) c

tutorialsarxiv-cs-lg

Omni-SafetyBench: A Benchmark for Safety Evaluation of Audio-Visual Large Language Models

arXiv:2508.07173v3 Announce Type: replace Abstract: Omni-modal Large Language Models (OLLMs) that integrate visual, auditory, and textual processing face severe safety risks. They exhibit fragile defe

StrategyBench: Evaluating Explicit Strategy Induction in Large Language Models

arXiv:2608.23475v1 Announce Type: new Abstract: As large language models are increasingly used in data-scarce and evolving task scenarios, few-shot in-context learning (ICL) has become a key paradigm

Uncertainty propagation in auto-regressive random neural network models

model-releasesarxiv-cs-lg

arXiv:2608.20483v1 Announce Type: cross Abstract: We develop analytical and particle-based methods for uncertainty propagation in random neural network models, where both the inputs and network parame

24 Aug 2026

CADRE: Stable, Parameter Efficient Adaptation of Medical Vision Language Models with Bounded Forgetting and Prior Drift

arXiv:2606.23487v2 Announce Type: replace Abstract: Medical vision-language models (VLMs) such as BiomedCLIP generalize broadly, but adapting them to a clinical service is as much a safety problem as

Exact Algebraic Computation of Learning Coefficients for Two-Dimensional Singular Models

arXiv:2608.20183v1 Announce Type: new Abstract: Classical information criteria such as the Bayesian Information Criterion (BIC) rely on regularity assumptions that break down for singular models, lead

ROBOSHACKLES: A Safety Dataset for Human-Injury Prevention in Embodied Foundation Models

model-releasesarxiv-cs-ro

arXiv:2606.18632v2 Announce Type: replace Abstract: Embodied Foundation Models (EFMs) integrate multimodal understanding, future-state reasoning, and executable robot actions. Yet their safety alignme

Rule-Compliant Visual Spatial Planning for Multimodal Large Language Models

arXiv:2608.20237v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) combine linguistic reasoning with visual perception, yet their ability to perform visual spatial planning under

Off-Manifold Collapse in Guided Protein Language Models

arXiv:2608.18597v1 Announce Type: new Abstract: Protein language models are widely used priors for protein sequence design, and a growing body of work controls them at inference time as an alternative

researcharxiv-cs-lg

20 Aug 2026

Safety

When Safety Overrides Vision: Exploring Dynamics between Vision Influence and Safety Alignment in Vision-Language Models

arXiv:2608.18628v1 Announce Type: cross Abstract: Aligned vision-language models (VLMs) are designed to balance grounded visual reasoning with safe generation behavior. However, we observe a striking

safetyarxiv-cs-cl

20 Aug 2026

JUMP: Single-Pass Membership Inference on Fine-Tuned Diffusion Language Models

arXiv:2607.16207v2 Announce Type: replace Abstract: Public open-weight language models are often fine-tuned on private or domain-specific data before deployment, creating a need to audit whether indiv

researcharxiv-cs-ai

19 Aug 2026

LinCa: Accelerating Diffusion Models via Learnable Decomposed Feature Caching

model-releasesarxiv-cs-cv

arXiv:2608.17973v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in image and video generation, yet the high computational cost of iterative sampling remains a critica

19 Aug 2026

MS-MFAD : Multimodal large language models for Face Anti-spoofing Detection

model-releasesarxiv-cs-cv

arXiv:2608.17328v1 Announce Type: new Abstract: Facial biometric recognition systems currently face compound threats intertwining generative AI and high-fidelity physical spoofing. Existing defenses s

19 Aug 2026

ALPS: Measuring Valid Creativity in Large Language Models with Mathematical Construction

arXiv:2608.15979v1 Announce Type: new Abstract: Large language models produce outputs presented as discoveries - new proofs, conjectures, or molecules. Whether such an output that appears creative is

An Empirical Study of Training Pixel-Space Text-to-Image Diffusion Models

arXiv:2608.16887v1 Announce Type: new Abstract: This paper investigates an increasingly important topic in generative modeling: pixel-space diffusion models. Although numerous studies have explored th

researcharxiv-cs-cv

Bactrainus: Optimizing Large Language Models for Multi-hop Complex Question Answering Tasks

arXiv:2501.06286v2 Announce Type: replace-cross Abstract: Multi-hop question answering requires a system to identify and integrate evidence distributed across documents, yet large language models rema

CACSurv: Concordance-Aligned Comparative Learning with Large Language Models for Cancer Survival Prediction

arXiv:2608.16594v1 Announce Type: new Abstract: Cancer survival prediction supports treatment planning, risk stratification, and follow-up management. Existing methods use structured clinical variable

Conditional Evaluation of Language Models with Cheap Auxiliary Signals

model-releasesarxiv-cs-lg

arXiv:2608.16210v1 Announce Type: new Abstract: Aggregate accuracy hides where models succeed and fail. Estimating conditional performance profiles from gold labels alone is expensive, while cheap aux

Safety

DR.GAP: Mitigating Bias in Large Language Models using Gender-Aware Prompting with Decoupled Reasoning

arXiv:2502.11603v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit strong natural language understanding capabilities but also inherit and amplify societal biases, particul

safetyarxiv-cs-ai

Global Federated Learning Strategies for Building Efficient Personalized Models

arXiv:2608.15107v1 Announce Type: new Abstract: Federated learning (FL) is a practical framework that can train models on distributed user data while guaranteeing data privacy; however, due to heterog

L3Cube-IndicQuest v2: A Large-Scale Multilingual Benchmark for Evaluating Factual Knowledge of Large Language Models Across Indic Languages

arXiv:2608.15535v1 Announce Type: new Abstract: We present L3Cube-IndicQuest v2, a large-scale gold-standard multilingual question-answering benchmark for evaluating the India-specific factual knowled

Low-Rank Dynamics-Effective Latent Carriers for Counterfactual Rollout in Learned World Models

arXiv:2608.15156v1 Announce Type: cross Abstract: World models may predict the future without making clear which parts of their hidden state actually drive those predictions. We ask whether a small, d

local-aiarxiv-cs-ai

SL-S4Wave: Self-Supervised Learning of Physiological Waveforms with Structured State Space Models

arXiv:2606.19888v2 Announce Type: replace-cross Abstract: Modeling long-sequence medical time series data, such as electrocardiograms (ECG), poses significant challenges due to high sampling rates, mu

local-aiarxiv-cs-ai

Vision Language Models Cannot Plan, but Can They Formalize?

arXiv:2509.21576v2 Announce Type: replace Abstract: The advancement of vision language models (VLMs) has empowered embodied agents to accomplish simple multimodal planning tasks, but not long-horizon

Wiola 13M, a Gated Spiral Attention Architecture for Parameter Efficient Small Language Models

arXiv:2608.14604v1 Announce Type: cross Abstract: Small language models in the ten to one hundred million parameter range are attractive for on device inference, rapid experimentation, and controlled

A Unified Assessment of the Poverty of the Stimulus Argument for Neural Language Models

arXiv:2602.09992v2 Announce Type: replace-cross Abstract: Several recent contributions have evaluated the Poverty of the Stimulus Hypothesis (PoSH) using Artificial Neural Networks (ANNs). The results

17 Aug 2026

Are Large Language Models Reliable Reviewers? A Benchmark for Error Detection in Financial Documents

arXiv:2608.12342v1 Announce Type: new Abstract: Ensuring the accuracy of financial documents is critical for economic analysis, regulatory compliance, and corporate decision-making. Several studies ha

Are you Talking Logic to Me? Assessing Language Models Syllogistic Reasoning Capabilities

arXiv:2608.12374v1 Announce Type: cross Abstract: Language models (LMs) struggle with logical tasks like reasoning on syllogisms. It has been shown that Knowledge Representation (KR) plays a crucial r

researcharxiv-cs-ai

Behavioral Reprogramming of Open-Weights Models: Cognitive Plasticity and Alignment Bounds

arXiv:2608.13069v1 Announce Type: new Abstract: Large language models (LLMs) are predominantly aligned to function as passive, sycophantic assistants. We challenge this default paradigm by empirically

FIRE-VLA: Failure-Informed Self-Evolution for Vision-Language-Action Models in Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2608.13395v1 Announce Type: new Abstract: Reinforcement learning improves autonomous-driving vision-language-action (VLA) models by evaluating trajectories sampled from the current policy. Group

Large Language Models Pass the History Exam But Miss the <<History>>: A Polish High School Exit Exam Matura Benchmark

arXiv:2608.12343v1 Announce Type: new Abstract: AI chatbots are widely used by students as knowledge sources, yet LLM benchmarks rarely assess interpretative historical reasoning. We evaluate eight le

Novels generated by language models show compressed formal variation

arXiv:2608.12630v1 Announce Type: cross Abstract: While large language models can generate entire novels, there is little information about the level of formal variation in their output over many gene

Safety

Scaling Automatic Research Agents via World Models

arXiv:2608.12564v1 Announce Type: new Abstract: Automating empirical research is a long-standing direction of AI. Recent automatic research (AutoResearch) agents bring this goal within reach, as moder

safetyarxiv-cs-lg

Can Vision Models Read the Radar Display? On the Feasibility of Radar Imagery for Air Traffic Complexity Estimation

arXiv:2608.11810v1 Announce Type: new Abstract: Air traffic controllers perceive traffic complexity through the radar display, suggesting that a computer vision model operating on the same imagery may

researcharxiv-cs-cv

CT-DeltaBench: A Benchmark for Longitudinal 3D Medical Imaging Difference Reporting with Vision-Language Models

arXiv:2608.11534v1 Announce Type: new Abstract: In medical imaging, the clinical value of Computed Tomography (CT) lies not only in depicting current disease status, but crucially in enabling longitud

How effective are VLMs in assisting humans in inferring the quality of mental models from Multimodal short answers?

arXiv:2603.00056v2 Announce Type: replace-cross Abstract: STEM Mental models can play a critical role in assessing students' conceptual understanding of a topic. They not only offer insights into what

researcharxiv-cs-ai

Orientation, not magnitude: the causal structure of task-vector interference in merged language models

model-releasesarxiv-cs-lg

arXiv:2608.11797v1 Announce Type: new Abstract: Model merging by task arithmetic works until it doesn't, and the field diagnoses why with magnitudes: layerwise representation bias, deviations from cro

Semantic Lenia: Emergence of Homeostatic Solitons within the Semantic Space of Large Language Models

arXiv:2608.11657v1 Announce Type: cross Abstract: We introduce Semantic Lenia, an artificial life framework that transforms Large Language Model (LLM) inference from a static optimization problem into