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artificial intelligence

14,560 papers

#artificial intelligence Preprint Open access Oct 2026

The AI Accountability Ecosystem in the Era of Language Models

This article reviews and updates the framework for accountability in AI based on account- ability ecosystems. We update the framework in light of the latest developments since the release of Large Language Models for general public use. We propose three interlinked updates to the original AI accountability ecosystem: (...

Chris Percy, Artur d'Avila Garcez · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Site Is Decodable Before Pretraining: Negative Controls for Probing Frozen Brain-MRI Foundation Models

Brain foundation models are often tested with a probe. The model is frozen, a simple classifier is trained on its output, and the classifier's accuracy is taken as a sign of what pretraining learned. We show that this reading can be wrong unless two controls are reported with it. We probed three frozen 3-D brain-MRI mo...

Saman Rahbar · 0 citations
#artificial intelligence Preprint Open access Oct 2026

MemArena: An Ego-Centric Benchmark for On-Device Agentic Personal Memory Assistants at Scale

Edge-deployed personal memory assistants must handle private interpersonal conversations on-device with open-weight models. Yet, existing memory benchmarks often under-test the combination of activity-dense interaction, ego-centric perspective, and coherent multi-session worlds. MemArena fills these gaps with a single-...

Jiadong Zhang, Xiaosong Ma · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Cost-Effective Automated Judging of Natural-Language Mathematical Proofs

Grading natural-language mathematical proofs is a recurring cost in evaluating math-reasoning systems, and frontier LLM judges are expensive. We ask whether cheap open-weight models can serve as reliable judges given a candidate proof, a ground-truth proof, and a human-grading rubric. On a 200-instance validation sampl...

Benjamin Grayzel · 0 citations
#artificial intelligence Preprint Open access Oct 2026

The Implementation Lottery: Auditing Idea Reliability in Automated Research

Automated research agents use program scores to judge ideas. We call variation in this evidence across implementations the implementation lottery. We introduce an Idea Reliability Audit that freezes mechanism specifications, samples independent programs, and compares selected code with fresh implementations of its mech...

Jingjie Ning, Shanshan Zhong, Xiaochuan Li et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

CAS I: A Geometric Coding Theorem

This paper establishes a direct analogue of the classical Coding Theorem in the setting of symmetry groups. We consider computable bijections on the set of binary strings and define the symmetry prior of a string x as the probability that a randomly chosen symmetry from a given group G has x as its unique fixed point....

Romie Banerjee · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Exact and Certified Data Shapley for Weighted Nearest Neighbor Regression

Data Shapley can be computed exactly and efficiently for unweighted K-nearest-neighbor (KNN) models, the basis of the popular KNN-Shapley. For weighted KNN, however, efficient exact algorithms are known only for hard-label classification. In regression, the prediction is a weighted average whose normalization term chan...

Zongye Lyu, Lihua Peng · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Authority-Bound Governance of Heterogeneous AI Security Decisions in Telecom and IoT Networks

Artificial intelligence (AI)-enabled security decision systems in telecom and IoT networks can draw on heterogeneous models whose outputs may trigger operational actions. Recording such decisions on a blockchain does not establish that they are authorised, applicable, policy-consistent, or still valid at execution time...

Saviz Changizi, Nasibeh Mohammadzadeh, Mohammad Shojafar et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Safe Inference-Time Alignment via Lagrangian Reward Augmentation

Inference-time alignment steers a frozen language model during decoding using auxiliary reward signals, avoiding the cost of repeated weight updates. However, existing inference-time alignment methods typically optimize a single scalar score, so explicit safety constraints must either be ignored or encoded through manu...

Yaswanth Chittepu, Ativ Joshi, Sohini Chintala et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

AnyGroundBench: A Multi-Domain Adaptation Benchmark for Video Grounding in VLMs

Vision-Language Models (VLMs) have shown strong performance in Spatio-Temporal Video Grounding (STVG), yet they are still evaluated mostly in a zero-shot manner on general-purpose benchmarks of everyday scenes. This creates a critical disconnect from real-world applications in specialized domains, where models inevitab...

Rintaro Otsubo, Ryo Fujii, Reina Ishikawa et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Office Comprehension Benchmark

We introduce Office Comprehension Bench (OCB), the first public benchmark to jointly evaluate LLM systems on Word, Excel, and PowerPoint comprehension over native file formats (.docx, .xlsx, .pptx) and their variants. OCB consists of two tracks. File Fidelity Q&A tests structural and visual perception of office artifac...

Firoz Shaik, Mateus Pican\c{c}o Lima Gomes, Tanvir Aumi et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Meta-Transfer Learning for mmWave Beam Alignment

Millimeter-wave (mmWave) beam alignment is critical for next-generation wireless systems, but existing approaches either update all parameters during adaptation or restrict updates to a subset of layers without adapting intermediate feature representations. We propose MTL-BA, a meta-transfer learning framework for mult...

Ahmet Nuri Cevik, Sinem Coleri · 0 citations

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MIT News · Artificial Intelligence Sep 29, 2026

Who we become when we talk to machines

Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.

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