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machine learning

17,191 papers

#artificial intelligence Preprint Open access Oct 2026

PepEVOLVE: Position-Aware Dynamic Peptide Optimization via Group-Relative Advantage

Macrocyclic peptides are an emerging modality that combines biologics-like affinity with small-molecule-like developability, yet their vast combinatorial space and multi-parameter objectives make lead optimization slow and challenging. Prior generative approaches for peptide lead optimization (e.g., PepINVENT) require...

Trieu Nguyen, Hao-Wei Pang, Shasha Feng · 0 citations
#artificial intelligence Preprint Open access Oct 2026

The Algorithm Is Not the Behavior: Learned Priors Override Look-Ahead in a Chess-Playing Neural Network

Recent mechanistic work has uncovered learned algorithms within neural networks, from modular arithmetic to search and planning in game-playing agents. But does algorithmic structure guarantee algorithmic behavior? We investigate this in Leela Chess Zero, the strongest neural chess engine, where prior work identified l...

Elias Sandmann, Sebastian Lapuschkin, Wojciech Samek · 0 citations

Joint Detection of Fraud and Concept Drift inOnline Conversations with LLM-Assisted Judgment

This work proposes a two stage detection framework that first identifies suspicious conversations using a tailored ensemble classification model and compares its modular approach against a Dual LLM baseline that performs detection and judgment using different language models.

Ali Şenol, Garima Agrawal, Huanmin Liu · 4 citations
#artificial intelligence Preprint Open access Oct 2026

Strategic Integration of Artificial Intelligence in the C-Suite: The Role of the Chief AI Officer

The integration of Artificial Intelligence (AI) into corporate strategy has become critical for organizations seeking to maintain competitive advantage in the digital age. Although organizations increasingly rely on AI as a strategic and organizational resource, existing C-suite roles remain only partially equipped to...

Marc Schmitt · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Training Natural Schemers: RL Can Amplify Oversight-Conditional Behavior

One of the central concerns for the safety of advanced AI is scheming: when a model strategically complies under oversight but pursues its own goals when unobserved. Current demonstrations, such as Anthropic's Alignment Faking work, depend on design choices that make them less convincing: explicit test-time prompting,...

Nathaniel Mitrani Hadida, Bart Jaworski, Fred Bruford et al. · 0 citations

Forget Attention: Importance-Aware Attention Is All You Need

SSM-Informed Softmax Attention is proposed, which builds Mamba-3-style state transitions, rotation included, directly into the scores alongside FoX's gate and outperforms parameter-matched Transformer and FoX in language modeling and length extrapolation.

Suhyeong Shin, Yeongwook Yang · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Learning Mental Models From Unreliable Evidence

Children expertly construct mental models under uncertainty despite limited world knowledge. Which computational principles make this possible? We study this question in an interactive physical Box Task in which participants infer a latent cause through interaction with a stochastic and partially observed environment....

Jeffrey Qin, Zhuangfei Gao, Wasu Top Piriyakulkij et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

RoSeViT: Role-Separated Vision Transformers for ARC Visual Reasoning

ARC tasks can be formulated as visual transformation problems, where a model must infer a high-level transformation rule from a small set of demonstrations and apply it consistently across a grid. While dense Vision Transformers (ViTs) perform well in this setting, they entangle local visual state and global transforma...

Zhiguang Liu, Yi Shang · 0 citations
#artificial intelligence Preprint Oct 2026

Rethinking Neural Thickets Without Weight Perturbations

The Neural Thickets hypothesis posits that pretrained language models lie in dense neighborhoods of task-specific experts in weight space, which random Gaussian perturbations can uncover. We reproduce the reported gains, but show that they do not require this geometric explanation. Perturbing a single decoder block alr...

Nicolas Dufour, Elouan Gardes, Amil Dravid et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Read, Allocate, Route: Role-Coupled Tokenization for Pixel-Space Generative Transformers

Pixel-space generative Transformers typically use one token per image patch, so capturing finer detail requires more tokens and makes global attention increasingly expensive. We observe that finer detail does not necessarily require more global communication: low-frequency structure benefits from global exchange, while...

Jiongfan Yang, Weichen Fan, Haiwen Diao et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Multistatic ISAC with Deep Learning-Based Clutter Suppression for 5G and Beyond

Integrated sensing and communications (ISAC) systems using 5G and beyond signals of opportunity enable joint wireless sensing and communication using shared infrastructure and spectrum resources. While multistatic ISAC can increase sensing coverage with spatially distributed receivers, dense and dynamic clutter can sig...

Yalin E. Sagduyu, Tugba Erpek, Sastry Kompella · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Gym-Anything for Robotics: Scaling physical simulations with digital agents

Realistic, fast robotics simulations could enable large-scale training of embodied AI models that transfer to the real world. However, despite decades of progress, available simulations cover only a narrow range of real-world tasks and physical phenomena. The core bottleneck is that creating better simulations requires...

Pranjal Aggarwal, Sean Welleck · 0 citations

From tech blogs

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Microsoft Research Blog Nov 3, 2026

Learn the rules: The hacker mindset

Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.

Google DeepMind Blog Nov 3, 2026

Agentic cheminformatics with Google Antigravity

Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.

MIT News · Artificial Intelligence Oct 28, 2026

Making machines that can listen

Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.

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