The International Conference on Web and Social Media (ICWSM) - AAAI
ICWSM brings together researchers in the broad field of social media analysis to foster discussions about research.
Membership in AAAI
AAAI membership supports efforts to encourage and facilitate research, education, and development in artificial intelligence.
To Mix or To Merge: Toward Multi-Domain Reinforcement Learning for Large Language Models
arXiv:2602.12566v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) plays a key role in stimulating the explicit reasoning capability of Large Language Models (LLMs). We can achieve expert-level performance in some specific domains via RLVR, such as coding...
X-SYS: A Reference Architecture for Interactive Explanation Systems
arXiv:2602.12748v1 Announce Type: new Abstract: The explainable AI (XAI) research community has proposed numerous technical methods, yet deploying explainability as systems remains challenging: Interactive explanation systems require both suitable algorithms and system capabilities that maintain explanation usability across repeated queries,...
Optimal Take-off under Fuzzy Clearances
arXiv:2602.13166v1 Announce Type: new Abstract: This paper presents a hybrid obstacle avoidance architecture that integrates Optimal Control under clearance with a Fuzzy Rule Based System (FRBS) to enable adaptive constraint handling for unmanned aircraft. Motivated by the limitations of classical...
acl-org/acl-anthology
Data and software for building the ACL Anthology. Contribute to acl-org/acl-anthology development by creating an account on GitHub.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations - ACL Anthology
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts - ACL Anthology
Call for Expressions of Interest to Host ICAIL 2027
The International Association for Artificial Intelligence and Law (IAAIL) invites initial bids (expressions of interest) to host the 22nd International…
Compute Cluster | CAIS
The Center for AI Safety is launching an initiative to provide large-scale compute resources for ML safety research. Apply here.
Netflix
With nearly 150 million subscribers around the world, Netflix has a commanding lead in the streaming wars. But it’s also facing heavy competition from deep-pocketed conglomerates like Disney, Apple, and AT&T, and an ongoing wave of narrow, targeted streaming sites...
Policy
Tech is reshaping the world — and not always for the better. Whether it’s the rules for Apple’s App Store or Facebook’s plan for fighting misinformation, tech platform policies can have enormous ripple effects on the rest of society. They’re...
Film
Cinema isn’t just about the latest Disney/Pixar project or Star Wars spin-off. Memorable storytelling is happening all over the film industry, from Hollywood’s box-office-busting superhero smashes to small, innovative indie experiments. The Verge’s film section is here to help you...
Creators
YouTube, Instagram, SoundCloud, and other online platforms are changing the way people create and consume media. The Verge’s Creators section covers the people using these platforms, what they’re making, and how those platforms are changing (for better and worse) in...
Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework
arXiv:2602.13271v1 Announce Type: new Abstract: The increasing complexity and frequency of cyber-threats demand intrusion detection systems (IDS) that are not only accurate but also interpretable. This paper presented a novel IDS framework that integrated Explainable Artificial Intelligence (XAI) to enhance...
BEAGLE: Behavior-Enforced Agent for Grounded Learner Emulation
arXiv:2602.13280v1 Announce Type: new Abstract: Simulating student learning behaviors in open-ended problem-solving environments holds potential for education research, from training adaptive tutoring systems to stress-testing pedagogical interventions. However, collecting authentic data is challenging due to privacy concerns and the high...
LLM-Powered Automatic Translation and Urgency in Crisis Scenarios
arXiv:2602.13452v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed for crisis preparedness and response, particularly for multilingual communication. However, their suitability for high-stakes crisis contexts remains insufficiently evaluated. This work examines the performance of state-of-the-art LLMs and...
MIDAS: Mosaic Input-Specific Differentiable Architecture Search
arXiv:2602.17700v1 Announce Type: cross Abstract: Differentiable Neural Architecture Search (NAS) provides efficient, gradient-based methods for automatically designing neural networks, yet its adoption remains limited in practice. We present MIDAS, a novel approach that modernizes DARTS by replacing static architecture parameters...
Automated Generation of Microfluidic Netlists using Large Language Models
arXiv:2602.19297v1 Announce Type: new Abstract: Microfluidic devices have emerged as powerful tools in various laboratory applications, but the complexity of their design limits accessibility for many practitioners. While progress has been made in microfluidic design automation (MFDA), a practical and...
The Auton Agentic AI Framework
arXiv:2602.23720v1 Announce Type: new Abstract: The field of Artificial Intelligence is undergoing a transition from Generative AI -- probabilistic generation of text and images -- to Agentic AI, in which autonomous systems execute actions within external environments on behalf of...
EmCoop: A Framework and Benchmark for Embodied Cooperation Among LLM Agents
arXiv:2603.00349v1 Announce Type: new Abstract: Real-world scenarios increasingly require multiple embodied agents to collaborate in dynamic environments under embodied constraints, as many tasks exceed the capabilities of any single agent. Recent advances in large language models (LLMs) enable high-level cognitive...
Machine Learning Grade Prediction Using Students' Grades and Demographics
arXiv:2603.00608v1 Announce Type: new Abstract: Student repetition in secondary education imposes significant resource burdens, particularly in resource-constrained contexts. Addressing this challenge, this study introduces a unified machine learning framework that simultaneously predicts pass/fail outcomes and continuous grades, a departure from...
TAB-PO: Preference Optimization with a Token-Level Adaptive Barrier for Token-Critical Structured Generation
arXiv:2603.00025v1 Announce Type: new Abstract: Direct Preference Optimization is an offline post-SFT method for aligning language models from preference pairs, with strong results in instruction following and summarization. However, DPO's sequence-level implicit reward can be brittle for token-critical structured prediction...
Federated Inference: Toward Privacy-Preserving Collaborative and Incentivized Model Serving
arXiv:2603.02214v1 Announce Type: new Abstract: Federated Inference (FI) studies how independently trained and privately owned models can collaborate at inference time without sharing data or model parameters. While recent work has explored secure and distributed inference from disparate perspectives, a...
SuperLocalMemory: Privacy-Preserving Multi-Agent Memory with Bayesian Trust Defense Against Memory Poisoning
arXiv:2603.02240v1 Announce Type: new Abstract: We present SuperLocalMemory, a local-first memory system for multi-agent AI that defends against OWASP ASI06 memory poisoning through architectural isolation and Bayesian trust scoring, while personalizing retrieval through adaptive learning-to-rank -- all without cloud dependencies...