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artificial intelligence

14,110 papers

#artificial intelligence Preprint Open access Oct 2026

MAP4CS: A Multi-dimensional Data Pruning Framework for Efficient Code Retriever Fine-tuning

Retrieval-Augmented Generation (RAG) has become a cornerstone in software engineering for enhancing Large Language Models (LLMs) with domain-specific knowledge. However, adapting retrievers to evolving code repositories remains challenging due to the noise and redundancy inherent in massive code corpora. Standard fine-...

Yuxuan Chen, Mingwei Liu, Guangsheng Ou et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Elucidating the Space of Enzymatic Reaction: A Unified Benchmark and Pretrained Model

Existing reaction models primarily learn molecular transformations, whereas enzy- matic reactions depend jointly on molecular structure and catalytic function. We formulate this problem as learning an enzymatic reaction space linking reactants, products, and Enzyme Commission (EC) annotations. To characterize this spac...

Yutong Hu, Tianming Huang, Yanbo Zhao et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Can Jev be Your Q or Policy in Reinforcement Learning?

Foundation models supply reinforcement learning (RL) with priors that mitigate its longstanding weaknesses in sample efficiency and transfer, but their token-by-token generation makes queries sequential and costly. Jev, a recently released decision model, generates nothing and returns calibrated, typed answers in a sin...

Yi Ma, Tianpei Yang, Yaodong Yang et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Epistemic Disturbance in the Graph Model for Conflict Resolution: State-Preserving Actions, Four-Valued Assessments, and the Distinction between Capability and Intention

In the graph model for conflict resolution (GMCR), a decision maker (DM) either moves the conflict to another state or does nothing. The basic definitions leave inaction implicit, so every action that leaves the state unchanged is treated as doing nothing. Yet announcements, exercises, leaks and selective disclosures a...

Yukiko Kato · 0 citations
#artificial intelligence Preprint Open access Oct 2026

HI3D 3.0 (Twinkle3D): Object-specific 3D Asset Generation with High Resolution

Image-to-3D generation has become increasingly capable of producing objects that closely resemble the input image, and an outstanding challenge is to reproduce the depicted object itself, including the specific geometry that defines it. Inscriptions, brand marks, and repeated structures are frequently distorted or lost...

Ziying Li, Shengchu Zhao, Huiang He et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

DIAL-OPD: Learning More from Fewer Tokens in On-Policy Distillation

On-policy distillation (OPD) supervises student-generated trajectories with token-level teacher signals. Its sampled-token variant avoids the cost of full-vocabulary probabilities. Yet we find that training on fewer tokens can outperform full-token OPD, challenging the intuition that more supervision improves learning....

Anhao Zhao, Haoran Xin, Junlong Tong et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

SkillContrast: Difference-Guided Text Selection for Agent Skill Reranking

Similar agent skills can share instructions but differ in their conditions of use. Query-based text selection may retain shared instructions and omit these distinctions. We introduce SkillContrast, a training-free selector that compares retrieved skills and retains their differing text with local context for a pretrain...

Jiandong Ding, Honglei Ji, Ming Liu et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

One Skill Too Many: How Co-Installed Skills Conflict in Coding Agents

Coding agents are extended with agent skills, directories whose SKILL.md tells the model when and how to perform a task. Because skills come from independent sources (teams, developers, plugins, copied collections), an installed skill can be co-installed with a similar skill doing the same job, and the model picks betw...

Chaoliang Yan, Zihao Xu, Yuekang Li et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

LTBD: Learnable Trust-Boundary Delimiters for Prompt Injection Defense

Large language models (LLMs) perform remarkably well on complex tasks, yet remain highly vulnerable to prompt injection attacks, where malicious instructions embedded in external data can override user intent. Existing defenses remain limited by model fine-tuning requirements, vulnerability to adaptive attacks, or reli...

Luman Zhao, Minghui Xu, Yue Zhang et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Neural Networks for Temporal Pattern Recognition and Dynamic Arm Gesture Speed Estimation for Robot Control

Deploying intelligent robotic systems that interact with humans through gestures requires neural networks capable of recognizing diverse temporal patterns. We present a systematic benchmark of ten abstract sequential tasks--five permutation-invariant (set) and five order-dependent (sequence) problems--evaluated across...

Mil\'an Zsolt Bagladi, L\'aszl\'o Guly\'as · 0 citations
#artificial intelligence Preprint Open access Oct 2026

TAM: Task-Aware Memory Distillation for Efficient Spatiotemporal Prediction

Knowledge distillation enables efficient spatiotemporal prediction by transferring knowledge from an accurate teacher to a compact student. However, matching outputs or features independently for each sample leaves cross-sample predictive structure underused. Exploiting this structure requires representations and histo...

Yuqi Li, Xiaoqin Feng, Fan Xu et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Beyond Report Imitation: Clinically Aware Multi-Image Ultrasound Report Generation from Visible Evidence

Generating ultrasound reports from multiple images requires aggregating clinical evidence across views, yet archived key frames capture only part of the dynamic examination. Raw-report imitation is therefore misaligned with visual supervision: content that is clinically valid for the full examination may be unverifiabl...

Yuchen Yang, Xin Wang, Lufan Wang 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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