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artificial intelligence

14,515 papers

#artificial intelligence Preprint Open access Oct 2026

Confidence-Ordering Reversal under Contextual Priors in Neural Decoding

Contextual priors improve neural-to-language decoding by reshaping candidate scores. However, confidence is read from the same reshaped scores, so the errors a prior leaves behind can become more confident with no change in accuracy to reveal it. We study how a prior shapes confidence in speech retrieval on MEG-MASC an...

Xinyu Zhang, Sichao Liu · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Quantum Entangled Multimodal Fusion Networks (QEMFN): Resource-Aware Hybrid Vision-Language Fusion via Trainable Entanglement

Multimodal vision-language systems typically fuse image and text embeddings through classical operators such as concatenation, attention, bilinear pooling, or tensor interactions. We propose Quantum Entangled Multimodal Fusion Networks (QEMFN), a hybrid quantum-classical framework that introduces parameterized entangle...

Srikar Alla, Ali Shiri Sichani, Chi-Ren Shyu · 0 citations
#artificial intelligence Preprint Oct 2026

Learn2Play Bench: How Well Do LLM Agents Learn from Experience in Unfamiliar Environments?

Learning from experience is essential for LLM agents to adapt to unfamiliar and dynmaic environments. Evaluating this ability is therefore important for understanding how effectively agents acquire and use new knowledge. Existing benchmarks have sought to evaluate this ability, but they primarily evaluate tasks whose r...

Yi-Bo Li, Jin-Hang Qiu, Zhi Zheng et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Mathematical Proof Assistants for Teaching Logic: The LogiKEy Methodology

We report on an approach to teaching logic to mixed groups of computer science, mathematics, and philosophy students, based on the logico-pluralistic LogiKEy methodology, used for more than a decade in courses, summer schools, and tutorials. LogiKEy uses classical higher-order logic (HOL) as a universal metalogic in wh...

Christoph Benzm\"uller, David Fuenmayor, Luca Pasetto · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Which alloy composition,what process parameters? Inferring the recipe from optimized metallic microstructure and texture

The mechanical properties of a metallic alloy are set by its microstructure and texture: the size and shape of its grains and the orientation of their crystals. That structure is in turn set by a recipe, the alloy composition together with the processing parameters. Alloy development runs this chain forwards, tuning th...

Mahish K. Guru, Jan Bohlen, Louam Lemjid et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Partially Observable Zero-shot coordination by Predicting Intention of Partner

Zero-shot coordination in embodied settings requires acting while the partner is intermittently out of view, leaving existing methods with ambiguous partner representations and uncertainty over hidden partner states. We propose Predicting Intention of Partner (PIP) to jointly address these challenges. PIP uses a Joint-...

Jinnyeong Yang, Yuhwan Jeong, Hoyong Kwon et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Test-Time Agent Evolution for Long-Horizon Legal Reasoning

Legal intelligence aims to support reliable decision-making across long-horizon legal processes involving evolving case states and multiple roles. However, real-world legal deployment exhibits substantial case heterogeneity in facts, evidence, and procedural contexts, exposing the limitations of static agent strategies...

Haotian Chen, Shuaicheng Niu, Haocong Rao et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

ChartBmkAgent: Harness-Governed Multi-Agent Construction of Chart QA Benchmarks from Sparse Error-Taxonomy Specifications

Multimodal large language models (MLLMs) advance rapidly, while conventional benchmark development lags behind, delaying investigation of newly observed capability gaps. Such investigation requires an expressive task format and an on-demand construction process: information-rich charts make chart question answering (Ch...

Langxi Huang, Pingping Zhang, Lanyun Zhu et al. · 0 citations
#artificial intelligence Review Oct 2026

DSV-Mem: Evaluating Multimodal Memory in Professional Workflows for MLLM Agents

Conversational MLLM agents are increasingly expected to assist in professional workflows, from AI research and engineering design to product management and business operations. Yet this capability remains underexplored: existing benchmarks largely focus on informal, everyday interactions and personal-life scenarios fea...

Ji-Ke Zhong, Ritwick Chaudhry, Xuan-Bai Chen et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Beyond Corrected Memory: Execution Consistency in Multi-Agent Systems

Shared memory coordinates agents' actions, but correct records do not establish that those actions satisfy task requirements. Memory governance and failure diagnosis regulate or inspect recorded information; they do not by themselves establish whether it is sufficient to judge task duties. We define execution consisten...

Zhe Yu, Zixuan Wang, Peidong Wang et al. · 0 citations
#artificial intelligence Preprint Oct 2026

SpeedrunBench: Challenging LLM Agents with Video Game Speedrunning

Frontier LLM agents have been shown to be capable of solving increasingly complex tasks for which humans have measurable solutions. This begs the pertinent question of whether LLM agents can go beyond what humans have already solved. The ability to develop sophisticated strategies to tackle consequential problems becom...

Yoshinari Fujinuma, Keisuke Kamahori, Ryuto Koike et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Same Feedback, Different Answer: Measuring Run-to-Run Instability in Frontier-Model Customer Feedback Analysis

AI agents are increasingly being programmed to automate knowledge work over large collections of unstructured data. Such automation requires repeatability: when the underlying evidence is unchanged, the agent's categories, priorities, and counts should not shift materially between runs, even if each individual answer a...

Viraj Bagal, Raviraja Ganta, Prabhath Chellingi · 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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