Assertion Messages with Large Language Models (LLMs) for Code
Accepted at Proceedings of the 2025 Evaluation and Assessment in Software Engineering (EASE '25)
Ahmed Aljohani +2 more
openaire +2 more sources
Closing the Empirical Loop: Autonomous AI Agents Conduct End‐to‐end Research With Human Participants
A multi‐agent AI system autonomously executes the complete scientific workflow, from hypothesis to manuscript, across three psychological studies involving 288 participants. The system designs experiments, collects real world data, develops analysis pipelines, and writes manuscripts with theoretical rigor comparable to experienced researchers.
Gabrielle Wehr +6 more
wiley +1 more source
Recommender Systems in the Era of Large Language Models (LLMs)
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys) have become an important component of our daily life, providing personalized suggestions that cater to user preferences. While Deep Neural Networks (DNNs) have made significant advancements in enhancing recommender systems by modeling user-item interactions and ...
Zihuai Zhao +10 more
openaire +4 more sources
Cancer‐Associated BCL‐2 Mutants Reveal Mechanisms Towards Venetoclax Resistance
Venetoclax (VEN) resistance in chronic lymphocytic leukemia arises from diverse BCL2 mutations. We map mechanisms contributing to VEN resistance across common BCL‐2 variants. G101V and D103Y reduce drug binding and increase sequestration of pro‐apoptotic proteins. V156D blocks VEN allosterically.
Jonas Aufdermauer +9 more
wiley +1 more source
CLRe: A Synergistic Dual‐Engine Framework for One‐Step Retrosynthesis Prediction
CLRe uses a contrastive difficulty score to order pretrained seq2seq fine‐tuning for retrosynthesis. Reaction embeddings define the ranking score, and a cumulative easy‐to‐hard schedule expands from the easiest subset to the full training set while earlier examples remain active.
Tianhao Su +5 more
wiley +1 more source
Interactive platform for supporting clinical decision-making using large language models (LLMs)
Current healthcare systems face increasing workload, fragmented communication, and documentation burden, which contributes to delays and diagnostic errors in early triage.
Міріам Фандакова +2 more
doaj +1 more source
CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang +4 more
wiley +1 more source
Chinese semantic obfuscation blackbox jailbreak for domestic large models
Jailbreak attacks represent a significant security threat to large language models (LLMs). Current research on jailbreak vulnerability mining primarily focuses on foreign LLMs operating within an English language environment.
Xinxin Yue +5 more
doaj +1 more source
Neuromorphic Devices and Computing for Sensing, Memory, and Control
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu +2 more
wiley +1 more source
Evalita-LLM: Benchmarking Large Language Models on Italian
We describe Evalita-LLM, a new benchmark designed to evaluate Large Language Models (LLMs) on Italian tasks. The distinguishing and innovative features of Evalita-LLM are the following: (i) all tasks are native Italian, avoiding issues of translating from Italian and potential cultural biases; (ii) in addition to well established multiple-choice tasks,
Bernardo Magnini +6 more
openaire +3 more sources

