Search: “science”

Evaluating the Semantic Specificity of Representation Steering in Language Models

arXiv:2608.29431v1 Announce Type: new Abstract: Localized Representation Steering (LRS) is widely used to correct reasoning pathologies in large language models. However, standard benchmark evaluation

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DGX agent

arXiv:2606.12683v2 Announce Type: replace Abstract: Over the last decade, building human-level artificial general intelligence has moved from far-fetched speculation to being a concrete next-decade ta

agentsarxiv-cs-ai

1 Sept 2026

Local Ai

MANTLE: A Framework for Adaptive In-Situ Planetary Perception Using a Modular Uplink Principle

arXiv:2608.28724v1 Announce Type: new Abstract: Planetary surface exploration missions rely increasingly on autonomous robotic platforms capable of interpreting complex terrain to ensure safe navigati

local-aiarxiv-cs-cv

On the Prospects of Dynamic LLM Conversations in Software Development

arXiv:2608.30756v1 Announce Type: cross Abstract: Large language models (LLMs) have become an essential tool for assisting developers, yet we still lack knowledge on ways to effectively support their

PaperGym: Rubric-Centered Evolution for Research-Plan Generation

arXiv:2608.31119v1 Announce Type: new Abstract: Research planning is the decisive capability of AI scientists. Yet a research plan admits no verifiable answer, so reinforcement learning lacks the envi

Reference-Grafting Matches Fine-Tuning at Eliciting Sandbagged Capabilities

arXiv:2608.29458v1 Announce Type: cross Abstract: Sandbagging, in which a model deliberately underperforms on an evaluation despite retaining the underlying capability, threatens the safety evaluation

Tutorials

Rotational Equivariance in Machine Learning: A Comprehensive Tutorial

arXiv:2608.31045v1 Announce Type: new Abstract: Rotational symmetry is one of the most important structural principles in machine learning on 3D data. In applications ranging from physics and material

tutorialsarxiv-cs-lg

Self-Evolving Skills via Surrogate-Guided Solve-and-Reproduce

arXiv:2608.28638v1 Announce Type: new Abstract: Agent skills are portable packages of instructions and resources an agent consults at deployment. Self-evolving them fails in two ways today. First, ski

Two Centuries of Sexism in British Parliament: A Computational Analysis of Women's Representation in the Hansard Corpus

arXiv:2608.30485v1 Announce Type: new Abstract: The language a legislature uses to debate women's rights, even in favour of them, encodes systematic patterns of sexism that persist across two centurie

researcharxiv-cs-cl

Applications

Unknown Unknowns: Do Hidden Intentions in LLMs Evade Detection?

arXiv:2601.18552v2 Announce Type: replace Abstract: LLMs expand accessibility and provide wide-reaching access to information. Yet these interactions also create opportunities to embed subtle, goal-or

applicationsarxiv-cs-cl

Using Grounded Theory for Agent Behavior Analysis at Scale

arXiv:2608.30391v1 Announce Type: cross Abstract: Understanding agent behavior requires methods that scale to thousands of trajectories and surface new patterns in long, often unfamiliar tasks where p

agentsarxiv-cs-ai

Verification abundance, adjudication scarcity: what happens to mathematical knowledge when proof checking becomes free

arXiv:2608.28997v1 Announce Type: new Abstract: In May 2026 an OpenAI model produced a counterexample to the Erdos unit distance conjecture. Five mathematicians published a human-verified version the

Who Flips? Self- and Cross-Model Counterarguments Reveal Answer Instability in LLMs

arXiv:2606.16011v2 Announce Type: replace Abstract: Standard accuracy benchmarks evaluate whether large language models (LLMs) reach correct answers. However, they do not test whether models maintain

A Multimodal Dataset of Student Oral Presentations with Sensors and Evaluation Data

model-releasesarxiv-cs-cv

arXiv:2601.07576v2 Announce Type: replace-cross Abstract: Oral presentation skills are a critical component of higher education, yet comprehensive datasets capturing real-world student performance acr

Beyond Procrustes distances: a multilinear Gromov-Wasserstein distance capturing chirality

arXiv:2608.27774v1 Announce Type: cross Abstract: Efficiently and robustly analyzing shape data is critical across many scientific disciplines. While chirality is a fundamental property in numerous ap

Tutorials

Euclidean Fourier Neural Operators

arXiv:2608.28425v1 Announce Type: new Abstract: Fourier neural operators (FNOs) provide an efficient framework for learning mappings between function spaces as they are, by construction, independent o

tutorialsarxiv-cs-lg

Applications

Self-Explainable Multi-Label Graph Neural Network for Correlated Evidence Attribution

arXiv:2608.27574v1 Announce Type: new Abstract: Multi-label graph learning intends to capture the intrinsic complexity of real-world applications, where one sample is often related to multiple groups

applicationsarxiv-cs-lg

There and Back Again: Bidirectional Diffusion Bridges for Multimodality Translation

arXiv:2608.27885v1 Announce Type: new Abstract: Multimodality translation (e.g., text-to-image) is a core generative AI task. However, existing approaches (1) follow generative paths that do not direc

Applications

BPMN4CAI: A BPMN Extension for Modeling Dynamic Conversational AI

arXiv:2608.27149v1 Announce Type: new Abstract: Conversational AI systems, such as chatbots and virtual assistants, are becoming increasingly important to digital business processes. However, the esta

applicationsarxiv-cs-ai

Not Just Reason, Not Just Scan: Reinforcement Learning for Proactive Scientific Error Verification over Academic Paper

arXiv:2608.26596v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly capable scientific assistants, yet they remain far from fully autonomous research. This transi

Real-time virtual circuits for plasma shape control via neural network emulators: integration and testing in the MAST-U PCS

arXiv:2608.26216v1 Announce Type: cross Abstract: The deployment of advanced, AI-enabled control algorithms in tokamak experiments requires robust integration with existing plasma control system (PCS)

SPEAR: Distilling Domain-Adaptive Reasoning Skeletons via Sequential Symbolic Alignment in Reinforcement Learning

arXiv:2608.26550v1 Announce Type: new Abstract: Reinforcement learning-based knowledge distillation has the potential to transfer complex reasoning from teacher to student models, yet it currently fac

safetyarxiv-cs-cl

Surgical Video Generation From Diffusion to World Models: A Survey

arXiv:2608.26214v1 Announce Type: new Abstract: Surgical video data provides the primary training resource for models of intraoperative perception, surgical workflow understanding, and robotic decisio

safetyarxiv-cs-cv

The Reasoning Tax: Token Economics of LLM Reasoning Across Task Types and Deployment Contexts

arXiv:2608.26235v1 Announce Type: new Abstract: Accuracy-only benchmarking of reasoning-capable large language models misses a central deployment question: when do extended thinking tokens earn their

FrontierChallenge: Evaluating Scientific Workflow Completion

arXiv:2608.24979v1 Announce Type: cross Abstract: Scientific agents increasingly analyze data, execute code, and produce research artifacts, yet most benchmarks emphasize final answers, isolated progr

Generative Modeling: A Review

model-releasesarxiv-cs-lg

arXiv:2501.05458v3 Announce Type: replace-cross Abstract: We organize the generative-modeling literature around three classes of generators, corresponding to three distinct inferential tasks: estimati

MathAdv: What Theorem Provers Know, Reason, Formalize, and Generalize

arXiv:2608.25449v1 Announce Type: new Abstract: Formal theorem proving enables machine-verifiable evaluation of mathematical reasoning, yet existing benchmarks often emphasize aggregate proof accuracy

Trace Integrity for LLM Data Agents: A Vision for Auditable Structured Reasoning in Real-World Systems

arXiv:2608.26036v1 Announce Type: cross Abstract: Answer accuracy is an insufficient reliability signal for LLM data agents. In structured-data tasks, a benchmark-correct answer can be produced by an

Ollivier-Ricci Curvature of Riemannian Manifolds and Directed Graphs with Applications to Graph Neural Networks

arXiv:2604.14211v2 Announce Type: replace-cross Abstract: This thesis is an exposition of Ollivier-Ricci Curvature of metric spaces as introduced by Yann Ollivier, which is based upon the 1-Wasserstei

26 Aug 2026

AI University: An LLM-Powered Learning Assistant for Engineering---A Finite Element Method Case Study

arXiv:2504.08846v2 Announce Type: replace-cross Abstract: We introduce AI University (AI-U), a flexible framework for AI-driven course content delivery that adapts to a course's instructional style. A

LLM assisted writing deserves empirical evaluation

arXiv:2608.22124v1 Announce Type: new Abstract: LLM-assisted writing is often treated as a detection problem, as it raises questions about clarity, integrity, equity, and evaluation. An analysis of 69

agentsarxiv-cs-cl

Mitigating Bias in Large Vision-Language Models via Counterfactual Ensemble Decoding

arXiv:2608.21415v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable performance across a wide range of tasks; however, they often inherit social biases from

Neuro-Causal Factor Analysis

arXiv:2305.19802v2 Announce Type: replace-cross Abstract: Factor analysis (FA) is a statistical method for explaining how mutually dependent observed variables can be represented in terms of mutually

SchemaRouter: Field-Aware Tool Routing for Efficient Heterogeneous Agentic RAG

arXiv:2608.21375v1 Announce Type: new Abstract: Heterogeneous agentic retrieval-augmented generation (RAG) systems increasingly orchestrate external APIs, internal databases, vector stores, and graph

AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning

arXiv:2508.14313v4 Announce Type: replace-cross Abstract: Test-time scaling strategies for Large Language Models predominantly rely on either reinforcement learning with sparse outcome rewards or sear

24 Aug 2026

Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI

arXiv:2411.08881v3 Announce Type: replace-cross Abstract: AI-based systems, including Large Language Models (LLMs), impact millions by supporting diverse tasks but face issues like misinformation, bia

24 Aug 2026

Memory Augmentation Unlocks Efficient Chain-of-Thought Reasoning

arXiv:2608.21265v1 Announce Type: new Abstract: Large language models often rely on Chain-of-Thought (CoT) reasoning to solve complex tasks, but verbose reasoning traces introduce substantial inferenc

researcharxiv-cs-cl

24 Aug 2026

Tutorials

A Tool to Map AI Programs in the U.S.: A Snapshot from April 2026 and an Analysis of Requirements for AI Majors and Minors

arXiv:2606.12428v2 Announce Type: replace-cross Abstract: In this work, we locate and analyze existing undergraduate Artificial Intelligence (AI) programs in the United States in Spring 2026, creating

tutorialsarxiv-cs-ai

Hallucination as a Feature, not a Defect: Evaluating a multi-agent architecture to transform speculative language-model outputs into testable scientific hypotheses

arXiv:2608.19206v1 Announce Type: cross Abstract: Contemporary Large Language Models (LLMs) are increasingly aligned to suppress hallucinations, prioritizing factual retrieval over combinatorial creat

MidTool: Mid-training Data Synthesis for Agentic Tool Use

arXiv:2608.20314v1 Announce Type: new Abstract: Mid-training is increasingly recognized as a critical stage for shaping the capabilities of large language models. Recent work has shown that targeted m

agentsarxiv-cs-ai

Symposium: Trust via Auditable Records for Communities of AI Scientist Agents

arXiv:2608.19511v1 Announce Type: new Abstract: Symposium is a formal framework and practical implementation to record the operation of AI agents deployed by small scientific research communities. Sym

agentsarxiv-cs-ai

Virtual Sensing to Enable Real-Time Monitoring of Inaccessible Locations & Unmeasurable Parameters

arXiv:2412.00107v3 Announce Type: replace-cross Abstract: Real-time monitoring of safety-critical interior states is an open problem across energy, environmental and industrial systems where direct in

When Saying No Makes Better Videos: Designing Dual Gatekeeping for Pedagogically Grounded AI Content Creation

arXiv:2608.19812v1 Announce Type: new Abstract: To prevent the adoption of aesthetically polished but pedagogically flawed AI content, we study a video authoring pipeline featuring two layers of struc

A Comprehensive Review of Large Language Models for Nanophotonics: From Surrogate Modeling to Autonomous Design

arXiv:2608.18279v1 Announce Type: cross Abstract: Metasurfaces have revolutionized the development of photonic devices by enabling unprecedented precision in light manipulation. However, their design

agentsarxiv-cs-lg

Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements

arXiv:2608.18294v1 Announce Type: cross Abstract: An increasing number of scholars use AI to measure variables they subsequently include in downstream analyses. Although AI-measured variables are ofte

Decomposing Wrong-Consensus Agreement in LLM Self-Consistency: A GPT-4.1 Case Study

arXiv:2608.18795v1 Announce Type: cross Abstract: Majority voting over multiple LLM samples is widely used to raise answer accuracy, yet its gain varies erratically: on hard questions it can even back

DeepTCM1.0: A Multi-Expert AI Agent for Deciphering Mechanisms of Chinese Herbal Formulae Based on General Large Language Models

arXiv:2608.18103v1 Announce Type: cross Abstract: Background: Mechanistic elucidation of traditional Chinese medicine (TCM) compound formulas remains a central challenge in the modernization of TCM. C

How AI Prompts Can Teach Us About the Structure of Human Behavior

arXiv:2608.18265v1 Announce Type: cross Abstract: We introduce a general, easy-to-implement AI-based method for studying the structure and complexity of human behavior. We assign a large language mode