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artificial intelligence

14,475 papers

#artificial intelligence Preprint Open access Oct 2026

When Tools Lie: Reliability of Mathematical Agents Under Corrupted Tool Feedback

Mathematical problem solving often requires deterministic computational steps that agents delegate to tools and implicitly trust. Yet tools can fail silently, returning plausible but incorrect results. How well can agents detect and correct corrupted tool call outputs? We study this through a controlled corruption fram...

Kavienan Jegatheesan, Gayathri Lihinikaduarachchi · 0 citations
#artificial intelligence Preprint Oct 2026

When Plans Change Answers: Formalizing Cost-Accuracy Optimization for Semantic Queries

In semantic query engines, predicates are evaluated by machine-learned models, and the choice of a query plan affects not only the cost of a query but also its result. Existing systems either apply a fixed threshold to each semantic operator or tune accuracy per operator, without accounting for how errors propagate thr...

Kyoungmin Kim · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Decide Before You Look: Learning Which Retrieved Memories Deserve Pixels

Multimodal assistants answer questions from long-term memories that contain images. After retrieval, each retrieved image reaches the answering model either as pixels, at about a thousand visual tokens per image, or as a stored text proxy that often misses the detail the question asks about. We find that the benefit of...

Youxing LI · 0 citations
#artificial intelligence Preprint Open access Oct 2026

ReGraph: A Computational Account of Emergent Generalization in the "what" and "where" Dual Visual Streams

Where generalization capacity--the ability to extract context-invariant relational structures--first emerges remains a central question in AI and neuroscience. The foundation for this capacity lies upstream of the hippocampus, within the entorhinal cortex, where parallel pathways dissociate relational structure in the...

Hyewon Kang, Jungmin Lee, Ilgyu Lee et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Adapting Vision-Language-Action Models to Unknown Visual Disruptions During Execution

Visual disruptions can arise while a robot is executing a task, leaving a vision-language-action (VLA) policy to respond without knowing the disruption type or timing. We introduce Self-supervised Adaptation from Leftover Trajectories (SALT), which uses the leftover trajectory, the unexecuted part of the previous actio...

Ahin Lee, Jinwoo Seo, Youngsoo Jang et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Dynamic Alignment and Calibration for Multimodal Learning

Dynamic multimodal learning aims to learn robust representations by adaptively modeling information discrepancies across modalities. However, existing methods still suffer from two limitations: (i) static cross-modal alignment strategies usually impose uniform constraints on all samples while overlooking sample-wise va...

Jing-Hao Xu, Zhen-Hua Guo, Xiao-Feng Zhu et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Multimodal Knowledge Distillation for Gastric Adenocarcinoma Classification from Whole-Slide Images

Gastric adenocarcinoma (GA) is a leading cause of cancer-related mortality worldwide, and accurate histopathological subtype classification from whole-slide images (WSIs) is essential for effective treatment planning. While multimodal approaches that integrate pathology report text with WSIs can improve classification,...

Shrihari Dumbre, Bikash Santra · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Diverse Motion Customization via Control-based Dynamic Optimization

Despite recent advances in video generation, motion customization remains challenging due to content leakage, where appearance attributes from the reference video unintentionally propagate into the generated output. We identify this issue as a consequence of the generative process collapsing toward the reference video,...

Youngyoon Choi, Kihyun Kim, Jeongwoo Shin et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

IEEE 802.11bx - WLAN Intelligent Networking (WIN): Toward an AI-Ready Wi-Fi 9

Wi-Fi 9 is expected to go beyond mere communication and provide new services such as sensing or computation. At this juncture, Artificial Intelligence (AI) is taking a leading role in the definition of the 802.11bx amendment, named WLAN Intelligent Networking (WIN). In this tutorial, we survey the recent progress made...

Francesc Wilhelmi, Katarzyna Kosek-Szott, Szymon Szott et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Contrastive Learning for Aspect Representation towards Explainable Recommendation

In this work, we propose a novel recommendation model, CLARER (Contrastive Learning for Aspect Representation towards Explainable Recommendation) that integrates aspect features learned from textual reviews with rating information to improve the accuracy and explainability of recommendations. Our proposed framework lea...

Emrul Hasan, Chen Ding · 0 citations
#artificial intelligence Preprint Oct 2026

Later Is Better: Token Reduction for ViTs Under Distribution Shift

Training-free token reduction accelerates vision transformers by removing redundant tokens across layers, recovering most of the original accuracy at a fraction of the compute. These methods, however, are designed and evaluated primarily on clean data, and under real-world distribution shift their accuracy gap to the u...

Hyeong-Tae Cha, Hyungjun Yoon, Sung-Ju Lee · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Cleave: Scaling Tensor Program Optimization via Decoupled Algebraic Search and Operator Scheduling

Optimized kernels such as FlashAttention and FlashDecoding are crucial for accelerating today's large models. Most of them are handwritten by experts because existing ML compilers cannot match their efficiency. Producing such kernels requires fusing computations with multiple reductions, which requires both algebraic t...

David Pissarra, Jinkun Lin, Haitian Jiang et al. · 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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