All Articles
16176 articles total
Understanding User Experiences of Computer Use Agents: Design Space and Opportunities for Building Agent UX Prototypes
Analyzes the UX design space for computer use agents and introduces AgentUXlab, a tool for prototyping and evaluating agent user experiences.
Long-Term PM2.5 Forecasting Using a DTW-Enhanced CNN-GRU Model
Proposes a DTW-enhanced CNN-GRU model for stable long-term PM2.5 air quality forecasting in resource-constrained urban environments.
DeepVRegulome: DNABERT-based deep-learning framework for predicting the functional impact of short genomic variants on the human regulome
Introduces DeepVRegulome, a framework using fine-tuned DNABERT models to predict the functional impact of genomic variants on the human regulome.
RefBench-PRO: Perceptual and Reasoning Oriented Benchmark for Referring Expression Comprehension
Introduces RefBench-PRO, a benchmark for referring expression comprehension, and Ref-R1, an RL-based learning scheme to improve localization accuracy.
Deep Delta Learning
Presents Deep Delta Learning (DDL), a structured residual update for Transformers that enables targeted edits to the residual state, improving language modeling quality.
Measuring the State of Open Science in Transportation Using Large Language Models
Uses LLMs to automatically measure open science practices (code and data sharing) in transportation research, revealing low adoption rates.
Picasso: Holistic Scene Reconstruction with Physics-Constrained Sampling
Introduces Picasso, a physics-constrained scene reconstruction pipeline and dataset that ensures geometrically and physically plausible multi-object reconstructions.
Kuna: Decompiler Development in the Age of Coding Agents
Discussion on the development of the Kuna decompiler and how coding agents are influencing the field of reverse engineering.
Thanatos Rising
A Hacker News thread titled 'Thanatos Rising', though the snippet provides no substantive content for a technical analysis.
Representation Capacity-Matched QNN-SNN Twin Construction for Rate-Encoded SNNs
A research paper proposing a capacity-matched construction between QNNs and SNNs to provide a fair energy efficiency comparison for neuromorphic hardware.
A context-adaptive policy framework for robust and reactive robotic manipulation via uncertainty-aware imitation learning
Presents a context-adaptive policy framework for robotic manipulation using uncertainty-aware imitation learning and a Mixture of Experts (MoE) formulation.
COMPOL: A Unified Neural Operator Framework for Scalable Multi-Physics Simulations
Introduces COMPOL, a neural operator framework designed to improve the scalability and accuracy of multi-physics simulations using attention-based aggregation.
Localizing Persona Representations in LLMs
A study analyzing where personas are encoded in LLM representation spaces, finding that divergence primarily occurs in the final third of decoder layers.
Towards Understanding the Cognitive Habits of Large Reasoning Models
Introduces CogTest, a benchmark to evaluate human-like cognitive habits in Large Reasoning Models (LRMs) through their Chain of Thought (CoT) patterns.
TaylorPODA: A Taylor Expansion-Based Method to Improve Post-Hoc Attributions for Opaque Models
Proposes TaylorPODA, a model-agnostic local attribution method based on Taylor expansion to improve the explainability of opaque AI models.
Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening
An audit of AI resume screening tools finding that perceived fairness often stems from a lack of evaluative competence rather than actual neutrality.
Annotation-Assisted Learning of Treatment Policies From Multimodal Electronic Health Records
Introduces AACE, an annotation-assisted approach to causal policy learning for multimodal electronic health records to improve medical treatment decisions.
NSF pilots 4-year PhDs with industry research placements
The NSF is piloting a program to implement 4-year PhDs that include industry research placements to better align academic research with industry needs.
Logic for Programmers by Hillel Wayne
Logic for Programmers is a resource by Hillel Wayne focusing on applying formal logic to software development.
Sheet As Token: A Graph-Enhanced Representation for Multi-Sheet Spreadsheet Understanding
The Sheet As Token (SAT) framework improves multi-sheet spreadsheet understanding for LLMs by treating worksheets as unified semantic units and using a graph-enhanced representation.