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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 117
Behaviour analysis for large language model-driven agents
Understanding language-agent behaviour requires learning how actions are organised across a trajectory and how this organisation relates to context and outcomes.AgentTrace: Execution-Level Fingerprinting of Black-Box LLM Agents
Verifying the provenance of autonomous LLM agents is a critical security challenge.TTT in VLA Models: Exploring Training with Human Demonstrations
Long-horizon robot tasks require retaining and using past information.DELA: Learning Controllable Edits for Diffusion Language Models
Diffusion language models (DLMs) support bidirectional denoising and iterative refinement, but generation remains largely controlled by token-level masking schedules.Learning Nonlinear Waveform Fusion Across Scales for Integrated Sensing and Communication
Fixed source superposition and frequency partitioning constrain how communication content interacts with a probing reference in integrated sensing and communication (ISAC).ReMedI: Inference-Time Refinement and Self-Distillation for Controllable Molecular Optimization
In drug development, lead optimization must improve competing properties, such as increasing permeability and reducing toxicity, while limiting scaffold changes that could compromise the lead's…PersonaScienceBench: Evaluating Scientific Agents with Diverse Simulated Researchers
Scientific agents collaborate with researchers whose expertise and preferences differ, but benchmarks usually hold the collaborator fixed.Who Verifies the Tools? How Warped Formatters Mislead Agents and Their Verifiers
Agents and verifiers often rely on the text a tool prints, and that text can misrepresent what the tool actually did, even when the tool's computation is correct.REACT: Representational Early Analysis and Control of Chain-of-Thought Trajectories
Chain-of-thought (CoT) generation offers an opportunity to intervene before a reasoning model completes its answer.Tampered ML: Evaluating LLM Judgment of Machine Learning Research
One approach to accelerating progress on AI alignment is to automate parts of alignment research itself.ImageRSI: Verification-Driven Recursive Self-Improvement for Agentic Image Generation
Complex text-to-image requests remain difficult to satisfy reliably.MPQ: A Message-Passing View of Post-Training Quantization
Post-training quantization (PTQ) is a key technique for efficiently deploying large language models, as it compresses weights into low-bit representations without retraining.Beyond Data Schedule: Fast LLM Pretraining on Data Mixtures by Loss-Reweighting
Large language models often acquire specialized capabilities through successive pretraining stages, but these gains can come at the cost of forgetting earlier knowledge.Rethinking LoRA Initialization for Robust Asymmetric Learning Rates
Low-Rank Adaptation (LoRA) is often highly sensitive to learning-rate (LR) choices.Implicit Neural Representations for Variational Problems on Graphons
We propose a neural exploratory framework for variational problems over graphons, i.e., symmetric measurable functions $[0,1]^2 \to [0,1]$, that arise as limits of dense graph sequences.The LLENS Platform for On-Premises Large Language Model Agents in a Japanese University Hospital: Development and Evaluation Study
Large language model agents that use tools could take on part of the electronic health record and desk work that occupies physicians' time, but in many hospitals the medical information systems run…Sparsity-driven emergence of functional modularity in multitask neural networks
Neural networks can learn multiple tasks, but how learning organizes shared computation into specialized and reusable components remains poorly understood.MG-REPA: Multi-Granularity Representation Alignment for Generative Target Speaker Extraction
Generative target speaker extraction (TSE) models achieve high-quality extraction, but suffer from considerably slow training convergence.$Ψ$-0.6: Adaptive Streams of Thought in a Unified Vision-Language World Model
Humans reason about the physical world by flexibly combining different forms of inference as a problem unfolds.Searching with Sparse Histories: Cross-Task Architecture Search from Incomplete Search Logs and Zero-Cost Proxies
Neural architecture search (NAS) is expensive, but cross-task transfer can reduce costs by reusing knowledge from previous tasks.