AI & Machine Learning · Computer Science & AI
Artificial Intelligence
The newest papers in Artificial Intelligence that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
Get the few papers worth your time in Artificial Intelligence every morning.
Follow Artificial Intelligence and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 241
Task-evoked eye movements as candidate digital biomarkers of depression severity in adolescents and young adults
Objective digital measures of depression severity could complement conventional symptom assessments and facilitate more timely clinical evaluation.Judges Follow the Reference: The Derivation Gap in Verifying Tool-Call Arguments
Tool-call judges evaluate argument values proposed by LLM agents.Aligning Faithfulness for Theory-Scale Autoformalization
Autoformalization (AF) requires more than compilation: formal statements must preserve the meaning of their informal sources, a property known as faithfulness.EgoOmniWorld: Unifying Egocentric Understanding via Ego-Action-World Interactions
Egocentric video understanding spans diverse capabilities, modalities, and evaluation formats, yet these are often studied in isolation despite their tight coupling in real-world interaction.The Smart Buildings Challenge: Learning Foundation Models for Real-World Optimization at Scale
Buildings cause nearly 40\% of carbon emissions in the US.A Global View of How LLMs Value Human Time
Large language models (LLMs) increasingly act as personal assistants; however, little is known about how they capture national-level preferences on a global scale.The Geometry of Language Model Logits: Generic Structure and Learned Departures
Autoregressive language models produce, at every prediction step, a vocabulary-sized logit vector whose structure determines the conditional next-token distribution.Lost in Implicit Routing: How LLM Agents Fail to Load Relevant Skills at Scale
Reusable skills let LLM agents load task-specific instructions on demand, but they make execution depend on implicit routing over skill metadata.APTree: Extended Behavior Trees for Adaptive and Scalable Automated Robotic Task Planning in Construction
Task planning for robots in off-site construction prefabrication is primarily manual, leading to planning inefficiencies and reluctance to adopt robotic solutions.On Symmetry for Characterizing Agent Heterogeneity in Multi-Agent Systems
Understanding agent heterogeneity can inform the design of shared and agent-specific policy representations, however existing criteria provide no unified structural test.Input-Conditioned Search for Efficient Test-Time Scaling of Recursive Reasoners
People often tackle difficult problems by thinking more deeply or exploring more possibilities.Rethinking Quality in Large Language Model Routing: Security-Conditioned Model-and-Budget Selection
Large language model (LLM) routers reduce serving cost by choosing which model to call and how many output tokens to grant it for each query.Configuring RAG Systems: What Breaks, Where Originates, and How to Fix
Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for improving Large Language Model (LLM) by intertwining it with other components, such as a vector/graph database.Order-Consistent Latent Geometry for Reliable Short-Horizon Planning in World Models
Latent planners often rank candidate action sequences by terminal Euclidean distance to a goal latent.LLM Agents for Automated Post-Training via Structured Recipe Optimization
Automated post-training transforms pre-trained large language models (LLMs) into models capable of handling diverse domains by automatically constructing and optimizing a recipe of coupled decisions…The Many Morals of AI: The cautionary bias of North American news narratives in global perspective
The stories told about artificial intelligence (AI) play a central role in shaping public understanding, policy debates, and expectations about technological change.When More Objectives Make Identification Easier: The Role of Preferences and Feedback
Best-arm identification (BAI) aims to identify the optimal arm using as few samples as possible.Reading Right, Acting Wrong: Diagnosing Decision Failures of System One Models in Agent Loops
System One models choose an agent's next action by scoring a supplied set of options in a single pass.Compare to Correct: Pairwise-Guided Logit Adjustment for LLM Test-Time Scaling
Sampling-based test-time scaling enhances LLM reasoning by aggregating multiple reasoning paths for the same query.GeoMER: A Joint Euclidean-Hyperbolic Geometry Framework for Multimodal Emotion Recognition
Multimodal Emotion Recognition (MER) aims to understand human emotions by integrating information from multiple modalities such as speech and text.