Search: “science”

From the Fluency Fallacy to the Micro-to-Macro Validity Gap: Opportunities and Pitfalls of LLMs in Social Simulation

arXiv:2507.19364v3 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) into social simulation has generated considerable enthusiasm, but also raises substantial methodolog

safetyarxiv-cs-ai

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Multi-Functional Embedding Models for Funder Name Disambiguation in Scientific Publication Records

DGX agent

arXiv:2609.09984v1 Announce Type: new Abstract: Understanding the historical allocation and distribution of research funding advances our knowledge of how scientific research is supported across field

model-releasesarxiv-cs-cl

10 Sept 2026

Hardware

Ordinary, Reasonable Chatbots: Do AI Models Track Human Legal Judgments?

arXiv:2609.06769v1 Announce Type: cross Abstract: As people increasingly rely on artificial intelligence (AI) for guidance in their own lives, scholars, lawyers, and even judges have begun to consider

hardwarearxiv-cs-ai

T-Mem: Memory That Anticipates, Not Archives

arXiv:2606.15405v2 Announce Type: replace-cross Abstract: Long-term memory is essential for conversational agents to remain coherent across extended dialogues, follow through on commitments made many

To Mix or To Merge: Toward Multi-Domain Reinforcement Learning for Large Language Models

arXiv:2602.12566v4 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) plays a key role in stimulating the explicit reasoning capability of Large Language Models (LL

What Does a System Modify When It Modifies Itself?

arXiv:2603.27611v2 Announce Type: replace Abstract: When a cognitive system modifies its own functioning, what exactly does it modify: a low-level rule, a control rule, or the criterion that evaluates

xDailyBench: Benchmarking LLMs on Professional Consultation for Real-Life Problems

arXiv:2609.07784v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally

Benchmarking Dexterity of Multifingered Robot Hands: A Review and Perspective

model-releasesarxiv-cs-ro

arXiv:2609.05585v1 Announce Type: new Abstract: Robot hands are a key interface between AI and the physical world, making advances in robotic dexterity essential to realizing the vision of physical AI

Tutorials

Capsule Lens: Locating and Tracking Concept Geometry in Model Representations

arXiv:2609.05575v1 Announce Type: cross Abstract: Understanding how concepts are encoded in the internal representations of machine learning models is a central problem in mechanistic interpretability

tutorialsarxiv-cs-cv

Tutorials

Clustering and Pruning in Causal Data Fusion

arXiv:2505.15215v4 Announce Type: replace-cross Abstract: Data fusion, the process of combining observational and experimental data, can enable the identification of causal effects that would otherwis

tutorialsarxiv-cs-lg

Local Ai

Connectome-to-Function: Conditional Generative Latent Representations for Reservoir Computing

arXiv:2609.06093v1 Announce Type: new Abstract: Connectomes, graph-level maps of neurons and their synaptic connections, provide a structural basis for understanding how brain circuits support functio

local-aiarxiv-cs-lg

DataFlex-RL: An Evaluation Platform for RLVR Data Policies

model-releasesarxiv-cs-lg

arXiv:2609.06107v1 Announce Type: new Abstract: Data policies for reinforcement learning with verifiable rewards (RLVR) determine which rollouts are used, how strongly they are weighted, and which dom

Decomposition-Guided Diffusion Language Models for Inertial Confinement Fusion Prediction

model-releasesarxiv-cs-lg

arXiv:2609.07756v1 Announce Type: new Abstract: Inertial confinement fusion (ICF) is a leading pathway toward clean energy, but each shot at the National Ignition Facility costs on the order of one mi

From Human Labels to Literature: Semi-Supervised Learning of NMR Chemical Shifts at Scale

arXiv:2601.18524v2 Announce Type: replace Abstract: Accurate prediction of nuclear magnetic resonance (NMR) chemical shifts is fundamental to spectral analysis and molecular structure elucidation, yet

From Proxies to Fields: Spatiotemporal Reconstruction of Global Radiation from Sparse Sensor Sequences

arXiv:2506.12045v2 Announce Type: replace Abstract: Accurate reconstruction of latent environmental fields from sparse, indirect observations is a fundamental challenge across scientific domains, from

LATS: Levy Adaptive Tree Sampling for Feedback-Driven Diverse Target Discovery

arXiv:2609.06761v1 Announce Type: new Abstract: While diffusion models excel at capturing complex data distributions, scientific discovery often requires steering generation toward specific, uncharact

MetaKV: Adaptive KV Cache Compression for Constrained LLM Inference

arXiv:2609.07966v1 Announce Type: new Abstract: Key--value (KV) cache compression is an effective way to reduce the memory overhead of large language model (LLM) inference, particularly for long-conte

ReST-RL: Reinforcing LLM Reasoning through Unified Self-Training and Value-Guided Search

arXiv:2508.19576v3 Announce Type: replace-cross Abstract: With respect to improving the reasoning accuracy of LLMs, the representative reinforcement learning (RL) method - Group Relative Policy Optimi

TimeBlind: A Spatio-Temporal Compositionality Benchmark for Video LLMs

model-releasesarxiv-cs-cv

arXiv:2602.00288v4 Announce Type: replace Abstract: Fine-grained spatio-temporal understanding is essential for video reasoning and embodied AI. Yet, while Multimodal Large Language Models (MLLMs) mas

Do Androids Dream of Unseen Puppeteers? Probing for a Conspiracy Tendencies in Large Language Models

arXiv:2511.03699v2 Announce Type: replace Abstract: We investigate whether Large Language Models (LLMs) exhibit conspiratorial tendencies, whether they display socio-demographic biases in this domain,

researcharxiv-cs-cl

Hakken: Predicting future discoveries to fill the gaps in today's knowledge

arXiv:2609.04494v1 Announce Type: cross Abstract: We present Hakken, a domain-agnostic prediction and explanation system performing knowledge prediction, i.e., growing scientific knowledge by establis

Partial Inverse Design of High-Performance Concrete Using Cooperative Neural Networks for Constraint-Aware Mix Generation

arXiv:2512.06813v3 Announce Type: replace-cross Abstract: High-performance concrete (HPC) requires complex mix design decisions involving interdependent variables and practical constraints. While data

The Sample Complexity of Learning Lipschitz Operators with respect to Gaussian Measures

arXiv:2410.23440v4 Announce Type: replace Abstract: Operator learning, the approximation of mappings between infinite-dimensional function spaces using machine learning, has gained increasing research

WaveletDiff: Multilevel Wavelet Diffusion For Time Series Generation

arXiv:2510.11839v3 Announce Type: replace Abstract: Time series are ubiquitous in many applications that involve forecasting, classification and causal inference tasks, such as healthcare, finance, au

applicationsarxiv-cs-lg

When Load-Balancing Goes Too Far: Expert Pruning in Over-Dispersed Mixture-of-Experts Models

arXiv:2609.04453v1 Announce Type: cross Abstract: Expert pruning reduces the memory and serving cost of Mixture-of-Experts (MoE) models by removing low-importance experts identified by the router, ass

Beyond .WAV: Design and Software Verification of VocalCap, a Traceable Browser-Based Audio Capture System for Vocal Biomarker Research

arXiv:2609.03320v1 Announce Type: cross Abstract: Remote voice studies often retain a final audio file with limited evidence about how it was captured, transferred, processed, and accepted. This paper

applicationsarxiv-cs-lg

From Euclidean to Graph-Structured Data: A Survey of Collaborative Learning

arXiv:2609.02984v1 Announce Type: new Abstract: The conventional approach to machine learning, that is, collecting data, training models, and performing inference in a single location, faces fundament

applicationsarxiv-cs-lg

From Zero to Hero: An Open LLM Ecosystem for Armenian

model-releasesarxiv-cs-cl

arXiv:2609.03350v1 Announce Type: cross Abstract: Pretraining data for Armenian, a morphologically rich and low-resource language, is scarce, and no open Armenian LLM has been released with the data a

GeoNatureAgent Benchmark: Benchmarking LLM Agents for Environmental Geospatial Analysis Across Frontier and Open-Weight Foundation Models

arXiv:2606.12821v2 Announce Type: replace Abstract: Environmental scientists spend disproportionate effort on data wrangling rather than analysis. New AI agents can be a helpful tool, but no benchmark

Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review

arXiv:2312.09454v3 Announce Type: replace-cross Abstract: Purpose: Uncertainty Quantification (UQ) has gained traction in an attempt to improve the interpretability and robustness of machine learning

Efficient Context-Limited Telescope Bibliography Classification for the WASP-2025 Shared Task Using SciBERT

arXiv:2609.01647v1 Announce Type: new Abstract: The creation of telescope bibliographies is a crucial part of assessing the scientific impact of observatories and ensuring reproducibility in astronomy

3 Sept 2026

A Mathematical Framework for Legacy, Governance, and Decision Integrity in Enterprise AI

arXiv:2609.00572v1 Announce Type: cross Abstract: Enterprise artificial intelligence is increasingly embedded in decisions that must remain lawful, explainable, adaptable, and accountable despite pers

applicationsarxiv-cs-ai

AI Should Not Only Be Helpful. It Should Be Contingent. Artificial Intimacy, Sycophancy, and the Future of Social Learning

arXiv:2609.00211v1 Announce Type: new Abstract: Conversational artificial intelligence is increasingly embedded in everyday social environments, where it functions as both an informational tool and a

safetyarxiv-cs-ai

Local Ai

An Intelligent Decision Support System for Emotion Monitoring using Microscopic Fixational Dynamics

arXiv:2609.00846v1 Announce Type: new Abstract: The rising prevalence of psychological disorders necessitates effective emotion monitoring, yet current methods relying on facial or physiological signa

local-aiarxiv-cs-cv

Autonomous discovery of new structure-plausibility laws for explainable and rapid crystal diagnosis and screening

arXiv:2609.01209v1 Announce Type: cross Abstract: Crystal generators and tool-using agents propose structures faster than density functional theory (DFT) energy and phonon calculations or experiments

Bridging Lexical Divergence: LLM-Assisted, Cost-Efficient, Zero-shot Scientific Entity Linking

model-releasesarxiv-cs-cl

arXiv:2609.00228v1 Announce Type: new Abstract: Scientific domain entity linking (EL) differs from general domain EL because mentions and entity names often lack lexical overlap. Another challenge is

From Terminology to Diagrams: Visual-Instruction Generation for Scientific Diagram Understanding

arXiv:2609.00948v1 Announce Type: cross Abstract: Vision-language models (VLMs) have demonstrated strong performance in visual question answering with natural images. However, they continue to struggl

ReproRepo: Scaling Reproducibility Audits with GitHub Repository Issues

arXiv:2606.18237v2 Announce Type: replace-cross Abstract: Reproducing research results from papers and released code is central to scientific progress. Existing works have introduced benchmarks to eva

Uncovering the Computational Ingredients of Human-Like Representations in LLMs

arXiv:2510.01030v2 Announce Type: replace Abstract: The human ability to translate diverse perceptual and linguistic inputs into structured behavior has been thought to rest on learning robust represe

A Multi-Agent Human-LLM Collaborative Framework for Closed-Loop Scientific Literature Summarization

arXiv:2604.01452v2 Announce Type: replace Abstract: Scientific discovery is slowed by fragmented literature that requires excessive human effort to gather, analyze, and understand. AI tools, including

Agnostics: Learning to Code in Any Programming Language via Reinforcement with a Universal Learning Environment

model-releasesarxiv-cs-lg

arXiv:2508.04865v4 Announce Type: replace Abstract: Large language models (LLMs) already excel at writing code in high-resource languages such as Python and JavaScript, yet stumble on low-resource lan

Arkios: An Open Bilingual English-Nepali Language Model Trained From Scratch, with a Devanagari-Aware Tokenizer

arXiv:2608.30092v1 Announce Type: cross Abstract: We present Arkios, a 1.04B-parameter dense transformer pretrained from scratch on 150B tokens of bilingual English-Nepali text, using a custom single-

Autoencoders in Function Space

arXiv:2408.01362v4 Announce Type: replace-cross Abstract: Autoencoders have found widespread application in both their original deterministic form and in their variational formulation (VAEs). In scien

Can LLM Agents Discover? Evaluating Creativity on ML Engineering Tasks

arXiv:2608.30047v1 Announce Type: new Abstract: Recent AI systems promise autonomous scientific discovery, claiming to discover algorithms and produce research papers, yet understanding whether they e

COGTRL: Training LLMs for Scientific Discovery Assistance using Cognitive Traces via Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2608.30109v1 Announce Type: new Abstract: Large Language Models (LLMs) trained on extensive scientific research are increasingly integrated as assistants for scientific discovery. However, most

Conservative Hybrid Graph Networks for Process Systems with Learned Routing

arXiv:2608.28896v1 Announce Type: new Abstract: Industrial process networks do not maintain a single effective topology while operating: streams are throttled or bypassed, and units move between idle,

Data-to-Energy Stochastic Dynamics

arXiv:2509.26364v3 Announce Type: replace Abstract: The Schrodinger bridge problem is concerned with finding a stochastic dynamical system bridging two marginal distributions that minimises a certain

DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editing

arXiv:2607.02290v2 Announce Type: replace Abstract: Recent image generation and editing models can produce visually appealing natural images, yet they remain unreliable when the target image is a know

researcharxiv-cs-cv