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Artificial Intelligence
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The newest 5,000 papers, from 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
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Newest papers, page 212
TIPS: A Tiny Inference-time Policy for Scaling in Diffusion Language Models
Masked diffusion language models expose an inference-time choice: which positions become visible after each denoising pass.PROBE: Learning to Audit Policy Compliance in Tool-Using LLM Agents
Modern agentic systems extend language models with external tools, enabling them to complete complex tasks through multi-turn interactions.Causal Integrated Gradients: Scalable Feature Attribution Along Causal Paths
Existing feature attribution methods that account for feature dependencies do not scale to high dimensions.Explaining the Roles of Experts in Mixture-of-Experts LLMs for Personalization
Personalization of Large Language Models (LLMs) is increasingly important for user-centric applications, yet prior methods mainly adapt dense LLMs, whose polysemantic neurons, each encoding multiple…DropKV: Decoupling Residual-Output Perturbation for Near-Optimal KV-Cache Eviction
Key-value (KV) cache management has become a critical bottleneck for scaling Large Language Models (LLMs) to long-context scenarios due to linear memory growth.CART: Compatible Routing for Multimodal Continual Instruction Tuning
Multimodal Large Language Models (MLLMs) achieve strong performance through instruction tuning, yet real-world applications often require them to continually acquire new capabilities from sequential…Believed but Not Said: Measuring Hidden Belief Collapse in Multi-Agent LLM Discussions
LLM systems increasingly rely on groups of agents that discuss, critique, and check one another, assuming that peers will catch individual errors.Are You Sure Your LLM Is Sure? Repairing and Auditing Confidence
Confidence scores determine whether an LLM answer is accepted, reviewed, or regenerated, yet scalar recalibration can only correct errors visible through the score itself.RAG-RST: Retrieved Exemplars as In-Context Discourse Schema for RST Parsing
In Rhetorical Structure Theory (RST), each edge of a discourse tree carries a nuclearity label, marking which span holds the central content, and a relation drawn from a closed inventory of…Specification Gaming and a Constrained Reinforcement Learning Mitigation in a Cleaning Gridworld
Reinforcement learning agents optimize exactly the reward signal they are given, which can diverge sharply from an intended true objective when that signal is only a proxy for it; this failure mode…Realtime-Bench: Can Frontier Models Solve Real-time Interactive Problems?
Real-time interaction requires agents to perceive evolving environments and act under temporal constraints, yet existing evaluations of real-time streaming models focus on conversational quality and…EMO: A Closed-Loop Test-Time Computation Framework via Alternating Context Optimization and Logits Steering
Test-time context optimization adapts frozen language models through textual feedback, but ordinary conditional generation provides no separate control over how strongly to reinforce the…Multi-sourced AI Tutor for Non-Native English Speaker Students
Large language models (LLMs) are increasingly being adopted as teaching tools in computing education, particularly for developing AI tutors capable of answering student questions.Mosaic: Multi-Session Agentic Reinforcement Learning
Most existing agentic reinforcement learning methods assume single-session trajectories, where interaction proceeds within one continuously accumulated context.Motion- and Gravity-Aware Feedforward 3D Reconstruction
Feed-forward transformer models have recently achieved strong performance in multi-view 3D reconstruction, but they still rely primarily on appearance-based attention and often struggle in dynamic…Whole-Body Dexterity
Current humanoid dexterous manipulation remains largely confined to end-effectors and simple grasps, falling short of humans' ability to engage the entire body by bracing and sliding bulky objects…Change the Number, Change the Answer: Assessing Rating Scale Sensitivity in LLM-Based Text Scoring
Large language models (LLMs) are increasingly used in computational social science to assign scalar scores to social and psychological constructs.Terminal-RSI: Recursive Self-Improving Terminal Agents via Recursive Self-Rewrite and Policy-Refine
Converting verifier outcomes into useful policy updates and partial progress into complete task resolution is crucial for terminal agents.AutoSFT: An Agentic System for Automated Data Research in Supervised Fine-Tuning
Language model agents increasingly automate post-training, but when given the full training stack they converge on supervised fine-tuning and spend most effort revising training data.HTN-Orchestrate: A Hierarchical Task Network Framework for Multi-Agent Orchestration
Orchestrating multiple agents on a complex task requires reconciling local subtask execution with global task planning.