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Artificial Intelligence
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The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,998 arXiv preprints and 2 OpenAlex records.
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Newest papers, page 86
Conservative Policy Iteration For Zero-Sum POSGs
Occupancy-state reductions make dynamic programming possible for zero-sum partially observable stochastic games (zs-POSGs).Evolving Agent Teams
The rapid progress of software engineering agents drives interest in applying them to open-ended problems such as GPU kernel optimization.When All Rollouts Fail: Policy-Compatible Joint Decoding for Hard-Problem Reasoning
Reinforcement Learning with Verifiable Rewards (RLVR) derives its learning signal from binary rewards via on-policy exploration and becomes a powerful paradigm for improving the reasoning of large…ActiveAlign: Aligning Egocentric Manipulation via Active Perception
Real-to-Sim-to-Real (Real2Sim2Real) enables structured world representations for planning, interpretability, and safe execution.AdaGround: Token-Normalized Adaptive Zooming with Verifier-in-the-Loop Refinement for GUI Grounding
GUI grounding on high-resolution screens fails mostly on small targets, and zooming in is a common training-free remedy.GUI-JEPA: Candidate-Conditioned JEPA Latents as a Fast Action Policy for Mobile GUI Agents
Mobile GUI agents are typically fine-tuned 7B-scale vision-language models (VLMs) that generate each action as text.RubricAtlas: Mining Type-Level Rubrics from Expert Reports to Evaluate Deep Research Agents
Deep research agents conduct multi-step Web searches and synthesise retrieved information into analytical reports.Noise Steering: Exploiting Wake Steering and Acoustic Directivity for Noise-Constrained Wind Farm Control via Reinforcement Learning
Existing noise mitigation strategies for wind farms usually consist in reducing turbines power output, without accounting for the wake interactions between them and the noise emission directivity.Natural Hard-Negative Mining from Positives for Instruction-Following Retrieval
Instruction-following information retrieval (IFIR) requires retrievers to rank documents by both a query and its instance-specific instructions, yet instruction-conditioned contrastive supervision…Developing a Speech Language Model for Basque
Although the recent development of LLMs has paved the way for multi-modal interaction, minority languages face difficulties keeping pace.Vision-Language Agents Can Learn in Their Own Latent Worlds
Learning from experience is essential for building the next generation of agents that continually expand their capabilities.Beyond QASecClaw: Agent Scaling, Verifier Feedback, and Evidence Reliability in Software Assurance
Can additional specialist language-model contexts improve software assurance when deterministic tool evidence is already available?Self-Keyed In-Parameter Memorization for External Memory-Free Dialogue Recall in Frozen Language Models
A large language model maintains conversational content in an external storage that is outside the model and grows as the dialogue continues.DCKV: Learned Transform Coding of the Prompt KV Cache in Hybrid Language Models
Hybrid language models keep a key-value (KV) cache only in their few full-attention layers, but this cache is still the part of a prompt's state that grows with the prompt and that must be stored or…Dense Representation Learning and Differentiable Shape Modeling for Spine Landmark Detection
Spine landmark detection from spinal X-ray is a key step for estimating spine deformation severity, for building biomechanical models, and for pre-operative planning.PailitaoMMSearch2.0 Technical Report: Scaling Generative Retrieval to Unified End-to-End Multimodal Search
Generative retrieval models have been increasingly adopted in search and recommendation systems.Do bots feel bad? Assessing empirical evidence for functional valence in LLMs
Do LLMs have valenced states, i.e. states that feel pleasant or unpleasant?Proactive Memory for Event-Driven LLM Agents
Proactive LLM agents anticipate service opportunities from ongoing observations and accumulated history.AutoVend: Benchmarking LLM Agents on Long-Horizon Autonomous Vending Operations
Large language model (LLM) agents are extending agent-mediated commerce on the Web from shopping for consumers to operating businesses for sellers.Advancement or Acceleration? How Data Curation Improves LLM Training
While data curation is widely credited with improving large language model training, a basic question remains unresolved: does curation expand what a model can ultimately learn, or merely reach the…