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Computation & Language / NLP
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The newest 5,000 papers, from 18 September 2026 to 6 November 2026: 5,000 arXiv preprints.
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Newest papers, page 166
CLM-as-a-Judge: Evaluating an Open Contrastive Decision Model on Public Judge Benchmarks
An open contrastive decision model is near chance as a judge on the hard public benchmarks: Contrastive-LM/CLM-v0.1-8B scores between 0.351 (best- of-four, chance 0.250) and 0.593 (pairwise, chance…Learning Scientific Exploration from Human Research Decision Trajectories
A key challenge in building AI systems for scientific research is enabling $\textit{scientific exploration}$: the systematic process of investigating unknown phenomena or ideas to gain new knowledge…Identifying Introspection From the Inside
Large language models make claims about themselves that are both consequential and increasingly difficult to verify from behavior alone.Responsible Institutional Analytics: Interpreting Bias with AI Support
Institutional Analytics (IA) dashboards inform decision-making in higher education, yet data limitations, constraints in analytical techniques, and missing contextual information often affect their…Forecasting the Growth of Social Media Information Cascades: Towards Human-in-the-Loop Misinformation Triage
Limited review teams must identify which emerging claims are likely to keep growing before their eventual reach is known.TIDE 2.0: an open, model-agnostic engine for keyed de-identification of clinical notes
Clinical notes capture most of what is documented about a patient's care, but they cannot be used for research until protected health information (PHI) is removed.Minimal Witness Reinforcement Learning
``What are the irreducible conditions that are sufficient to produce an outcome?'' is one of the most common questions that recur across computation and science.Lineage-Aware Memory Governance: A Derivation-Gated Framework for Privacy-Preserving Column-Level Access Control in Enterprise AI Agents
Enterprise AI agents that share a memory store face two unaddressed risks: sensitive data can leak through legitimately computed results the requester could not derive, and departments can silently…Kurate: Scalable Scientific Quality Analysis
Scientific search systems can find papers that are relevant to a question, but they generally do not assess the quality of the evidence that those papers provide.SharedKV-BT: Node-Local Typed Decisions for Behavior-Tree Agents
Agent tasks require sequences of interdependent decisions.Structuring MoE Expert Selection for Agentic Reinforcement Learning
Long-horizon LLM agents are frequently implemented using sparse mixture-of-experts (MoE) models, yet the co-design of agentic behavior and MoE structures remains underexplored.Logbook: Extremely Long-form Audio Event Understanding
Audio benchmarks are built around short, pre-segmented clips, limiting model design to brief inputs or fixed vocabularies.A doctrine-grounded visual question answering dataset for Tactical Combat Casualty Care
Tactical Combat Casualty Care (TC3) requires responders to connect visual observations of injuries and interventions with established clinical guidance.Stepped MoE: Segment-Level Routing with Configurable Inference Complexity
Training large language models (LLMs) is resource-intensive, and adapting them for diverse deployment scenarios with varying computational constraints remains challenging.Tracking Is Not Permanence: What Video World Models Keep of a Hidden Object
Video world models track objects they can see; we ask what they keep of objects they cannot.Who Wrote It Is Not Enough: Detecting Who Contributed the Insight
As LLMs increasingly assist scientific writing and peer review, detecting who wrote the text is no longer sufficient: we need to determine who contributed the underlying insight.AccentCL: Robust Accent Classification with Incremental Expansion
Accent classifiers are typically trained with a fixed label inventory and cannot accommodate new accent categories as new data becomes available.AlignQuant: Tile-Aligned Mixed-Precision Quantization for Efficient LLM Generation
Fine-grained mixed-precision quantization promises efficient large language model inference, but local precision choices can conflict with regular GPU storage and computation units.Auditable Claims about AI Agents
Organizations make claims about their AI agents: a person approves every external email, every action is logged, an evaluation shows the agent is safe to deploy.In With the Old: Enhancing 'Classical' Document Automation with Generative AI
Software-based legal assistance systems have leveraged many different forms of knowledge representation and reasoning.