Search: “science”

SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?

arXiv:2511.06090v3 Announce Type: replace-cross Abstract: Optimizing the performance of large-scale software repositories demands expertise in code reasoning and software engineering (SWE) to reduce r

30 Jun 2026

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The FIL Hypothesis: Inductive Biases Help with Kernel Engineering

DGX agent

arXiv:2606.30442v1 Announce Type: new Abstract: The Bitter Lesson, which posits that general-purpose methods that scale with computation and data ultimately outperform those with built-in human knowle

model-releasesarxiv-cs-ai

30 Jun 2026

Towards Physical Intuitions for Alignment Dynamics: A Case Study With Randomness Crystallization

arXiv:2606.29933v1 Announce Type: new Abstract: The alignment of language models is typically studied through the lens of capability benchmarks, but the dynamics of how models change during post-train

safetyarxiv-cs-cl

30 Jun 2026

Tutorials

Who Plays Which Role When? Communication Role Dynamics for Peer Recognition and Team Performance Prediction

arXiv:2606.28544v1 Announce Type: cross Abstract: Team roles offer an interpretable lens on collaboration, yet computational studies of roles often rely on domain-specific personas or data-driven clus

tutorialsarxiv-cs-cl

30 Jun 2026

Are Time-Series Foundation Models Ready for E-Nose Data? An Empirical Assessment of Their Embeddings

arXiv:2606.27672v1 Announce Type: new Abstract: Inspired by advances in natural language processing and computer vision, 'time-series foundation models' (TSFMs) have recently been introduced with the

applicationsarxiv-cs-lg

29 Jun 2026

Effects of relational graph modularity and depth on the learning performance of neural networks

arXiv:2507.10005v2 Announce Type: replace Abstract: In recent years, graph-based machine learning techniques, such as reinforcement learning and graph neural networks, have garnered significant attent

applicationsarxiv-cs-lg

29 Jun 2026

The Shift Toward Open and Reproducible AI Research

arXiv:2606.16974v3 Announce Type: replace Abstract: The reproducibility crisis has directed the AI research community toward improving documentation practices. Several studies have identified methodol

researcharxiv-cs-ai

29 Jun 2026

At the Edge of Understanding: Sparse Autoencoders Trace The Limits of Transformer Generalization

arXiv:2606.26396v1 Announce Type: new Abstract: Pre-trained transformers have demonstrated remarkable generalization abilities, at times extending beyond the scope of their training data. Yet, real-wo

Comparing BERT Sentence-Pair Classification and Few-Shot LLM Prompting for Detecting Threat and Solution Framing in German Climate News

model-releasesarxiv-cs-cl

arXiv:2606.26489v1 Announce Type: new Abstract: News media play a central role in shaping public perceptions of climate change, and whether coverage emphasizes threats or solutions has measurable effe

Estimating Uncertainty in Classifier Performance with Applications to Large Language Models and Nested Data

arXiv:2606.26422v1 Announce Type: new Abstract: Researchers increasingly use text classification--supervised models or large language models--to measure constructs from natural language, providing met

researcharxiv-cs-ai

Graph Neural Networks Applications Across Domains: All Insights You Need

arXiv:2606.27202v1 Announce Type: new Abstract: Graph neural networks have moved from a niche representation-learning technique to the default model class wherever data carry relational structure. The

Learning User Simulators with Turing Rewards

arXiv:2606.19336v2 Announce Type: replace Abstract: Learning to simulate human users in interactive settings could advance the training of agent assistants, evaluation of personalization systems, rese

agentsarxiv-cs-cl

Mapping Political-Elite Networks in Europe with a Multilingual Joint Entity-Relation Extraction Pipeline

arXiv:2606.27347v1 Announce Type: new Abstract: Whether political elites organise into rent-seeking coalitions that capture public resources or civic networks that sustain governance is a central ques

applicationsarxiv-cs-cl

RolloutPipe: Overlapping Pipelined Rollout and Training in Disaggregated On-Policy LLM Reinforcement Learning

arXiv:2606.26997v1 Announce Type: cross Abstract: Large language model (LLM) post-training for reasoning increasingly relies on reinforcement learning with verifiable rewards (RLVR), where models lear

Socratic agents for autonomous scientific discovery in high-dimensional physical systems

arXiv:2606.26722v1 Announce Type: new Abstract: The automation of scientific discovery has reached an inflection point. While AI systems now operate instruments, optimize parameters and generate hypot

The Open Source Economic Index of AI Adoption and Capability

arXiv:2606.26118v1 Announce Type: cross Abstract: We work towards measuring both AI adoption and the capability of AI to perform discrete labor tasks across various occupations. To measure adoption, w

Thinking Like a Scientist? A Structural Study of LLM-Generated Research Methods

arXiv:2606.26130v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to guide research methodology, yet their default methodological tendencies under minimal prompting

Autodata: An agentic data scientist to create high quality synthetic data

arXiv:2606.25996v1 Announce Type: cross Abstract: We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality training and evaluation data. We show

agentsarxiv-cs-cl

How Pragmatics Shape Articulation: A Computational Case Study in STEM ASL Discourse

arXiv:2510.23842v2 Announce Type: replace Abstract: Most state-of-the-art sign language models are trained on interpreter or isolated vocabulary data, which overlooks the variability that characterize

applicationsarxiv-cs-cl

On-Policy Self-Distillation with Sampled Demonstrations Reduces Output Diversity

arXiv:2606.26091v1 Announce Type: new Abstract: On-policy self-distillation achieves strong pass@1 accuracy by using a single model as both teacher and student, with the teacher conditioned on a corre

RWGBench: Evaluating Scholarly Positioning in Related Work Generation

arXiv:2606.24894v1 Announce Type: cross Abstract: Large language models have shown strong fluency in scientific writing, yet the evaluation of related work generation (RWG) remains limited. Existing R

Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR

arXiv:2606.25178v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has been extended from single-domain training to multi-domain reasoning suites spanning mathematic

safetyarxiv-cs-ai

Constrained Variable Projection for Structured Problems

arXiv:2606.23939v1 Announce Type: cross Abstract: Variable projection is a classical technique for separable nonlinear least-squares problems, in which variables that enter linearly are eliminated exa

Critique of Agent Model

arXiv:2606.23991v1 Announce Type: new Abstract: What is an agent? What constitutes agency? With the rise of Large Language Model (LLM) systems marketed as ``coding agents'', ``AI co-scientists'', and

safetyarxiv-cs-ai

Less is More: Quality-Aware Training Data Selection for Scientific Summarization

arXiv:2606.24828v1 Announce Type: new Abstract: Scientific long-document summarization datasets commonly treat author-written abstracts as gold reference summaries, although their quality and alignmen

safetyarxiv-cs-cl

Machine Learning and Deep Learning for Exoplanet Detection and Atmospheric Characterization with JWST and the Upcoming Ariel Mission

model-releasesarxiv-cs-lg

arXiv:2606.23766v1 Announce Type: cross Abstract: The detection and atmospheric characterization of exoplanets have entered a new data-intensive era driven by the James Webb Space Telescope and the up

PETRA: Transforming Web Text for Petroleum-Engineering Domain Adaptation

model-releasesarxiv-cs-cl

arXiv:2606.24346v1 Announce Type: cross Abstract: Petroleum-engineering search exposes a supervision gap for strong general retrievers: relevant evidence exists in public web text, but domain relevanc

Reinforcement Learning Towards Broadly and Persistently Beneficial Models

arXiv:2606.24014v1 Announce Type: new Abstract: As AI systems are deployed across increasingly diverse and high-stakes settings, model alignment must generalize beyond the tasks and domains seen durin

safetyarxiv-cs-ai

Adaptive Hard-Soft Physics-Informed Neural Networks for Robust Boundary-Constrained PDE Solving

arXiv:2606.23359v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide an effective way to solve partial differential equations (PDEs) by embedding physical principles into t

ARCO-Mars: A Unified Cloud-Optimized Archive of Mars Atmosphere Reanalysis

arXiv:2606.21701v1 Announce Type: cross Abstract: Long-term records of the Martian atmosphere based on general circulation models and reanalysis of atmospheric state variables are important to underst

Data-Driven Image Registration and Deformation Modeling for Image-Guided Neurosurgery: A Systematic Review

arXiv:2602.10155v2 Announce Type: replace-cross Abstract: Accurate compensation of brain deformation is critical for reliable image-guided neurosurgery. Surgical manipulation and tumor resection induc

safetyarxiv-cs-cv

Deep RL for Fast Long-Horizon Operations Scheduling on NASA's Carruthers Geocorona Observatory Mission

arXiv:2606.22159v1 Announce Type: cross Abstract: Spacecraft operations scheduling is a highly constrained, long-horizon combinatorial optimization problem that traditionally relies on heuristics, con

Discrete State Diffusion Models: A Sample Complexity Perspective

arXiv:2510.10854v3 Announce Type: replace Abstract: Diffusion models have demonstrated remarkable performance in generating high-dimensional samples across domains such as vision, language, and the sc

FCR: Investigating Generative AI models for Forensic Craniofacial Reconstruction

arXiv:2508.18031v2 Announce Type: replace Abstract: Craniofacial reconstruction in forensics is one of the processes to identify victims of crime and natural disasters. Identifying an individual from

researcharxiv-cs-cv

It's Much Easier for Neural Networks to learn Game of Life Dynamics with the Right Activation Function: Polynomial Kolmogorov-Arnold Networks

model-releasesarxiv-cs-lg

arXiv:2606.23587v1 Announce Type: new Abstract: Previous work has found a gap between the scale of neural networks that reliably learn Conway's Game of Life, and minimal networks capable of representi

Thalia: A Global, Multi-Modal Dataset for Volcanic Activity Monitoring

model-releasesarxiv-cs-cv

arXiv:2505.17782v4 Announce Type: replace Abstract: Monitoring volcanic activity is of paramount importance to safeguarding lives, infrastructure, and ecosystems. However, only a small fraction of kno

VRPO: Rethinking Value Modeling for Robust RL under Noisy Supervision in LLM Post-Training

arXiv:2508.03058v2 Announce Type: replace Abstract: Reinforcement Learning (RL) in real-world environments often suffers from ambiguous or incomplete reward supervision, which undermines policy stabil

Local Ai

A Multi-Modal Sensor Fusion Instrument for Measuring Regional Human Mobility: The Distributed Human Data Engine (DHDE)

arXiv:2603.21639v2 Announce Type: replace-cross Abstract: Accurately estimating human mobility in peripheral regional economies presents a fundamental measurement challenge: physical ground-truth sens

local-aiarxiv-cs-lg

A prior-free blind detection of information leakage from model predictions

arXiv:2606.11267v1 Announce Type: new Abstract: Data leakage -- contamination of a model with information unavailable at baseline -- is the dominant reproducibility failure in machine-learning-based s

Building Social World Models with Large Language Models

model-releasesarxiv-cs-cl

arXiv:2606.11482v1 Announce Type: cross Abstract: Understanding and predicting how social beliefs evolve in response to events -- from policy changes to scientific breakthroughs -- remains a fundament

FOCUS on Contamination: Hydrology-Informed Noise-Aware Learning for Geospatial PFAS Mapping

arXiv:2502.14894v5 Announce Type: replace-cross Abstract: Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with significant public health impacts, yet large-scale m

applicationsarxiv-cs-ai

LLMs+Graphs: Toward Graph-Native, Synergistic AI Systems

arXiv:2606.11560v1 Announce Type: cross Abstract: Large Language Models (LLMs) have advanced rapidly, but their limitations in structured and multi-hop reasoning underscore the need for graph-native,

Measuring language complexity from hierarchical reuse of recurring patterns

arXiv:2606.11531v1 Announce Type: new Abstract: We introduce the ladderpath index as a measure of language complexity grounded in algorithmic information theory. It counts the minimum steps needed to

researcharxiv-cs-cl

Notes2Skills: From Lab Notebooks to Certainty-Aware Scientific Agent Skills

arXiv:2606.11897v1 Announce Type: new Abstract: Scientific discovery workflows usually contain and rely heavily on lab notes, where researchers record observations, interpret uncertain results, and pl

agentsarxiv-cs-cl

PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework

model-releasesarxiv-cs-lg

arXiv:2505.08784v2 Announce Type: replace-cross Abstract: As machine learning (ML) enters high-stakes domains, trustworthy uncertainty quantification (UQ) is essential for safety. In this paper we int

Physics-informed generative AI for semiconductor manufacturing: Enforcing hard physical constraints in generative models by construction

arXiv:2606.11247v1 Announce Type: cross Abstract: Generative models are increasingly used to propose designs, data, and control actions for physical systems, yet many such systems are governed by hard

Belief Acquisition as Stochastic Filtering

arXiv:2206.02178v3 Announce Type: replace Abstract: This paper studies how belief acquisition can be accomplished using stochastic filtering. First, a theoretical foundation for empirical beliefs is o

researcharxiv-cs-ai

10 Jun 2026

Business World Model

arXiv:2606.10044v1 Announce Type: new Abstract: Businesses are increasingly adopting AI-enabled tools to improve productivity, reduce costs, and enhance products and services. However, the transformat