Search: “papers”

Fitting Is Not Enough: Smoothness in Extremely Quantized LLMs

arXiv:2605.08894v1 Announce Type: cross Abstract: Large language models (LLMs) achieve strong performance but incur high deployment costs, motivating extremely low-bit but lossy quantization. Existing

researcharxiv-cs-ai

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NeurIPS Should Require Reproducibility Standards for Frontier AI Safety Claims

DGX agent

arXiv:2605.08192v1 Announce Type: cross Abstract: Frontier AI safety claims - published assertions that a highly capable general-purpose model is below a threshold of concern, adequately mitigated, or

model-releasesarxiv-cs-ai

12 May 2026

PaperFit: Vision-in-the-Loop Typesetting Optimization for Scientific Documents

arXiv:2605.10341v1 Announce Type: new Abstract: A LaTeX manuscript that compiles without error is not necessarily publication-ready. The resulting PDFs frequently suffer from misplaced floats, overflo

Pay attention to this one if you build research or knowledge-work agents. Most research-agent systems produce uniform outputs regardless of …

Pay attention to this one if you build research or knowledge-work agents. Most research-agent systems produce uniform outputs regardless of who is driving them. This new work, NanoResearch, argues tha

safetydair-ai--x

Local Ai

Privacy-Preserving Distributed Learning in IoT Systems: A Unified Threat Model and Evaluation Framework

arXiv:2605.09232v1 Announce Type: cross Abstract: The increasing deployment of Internet-of-Things (IoT) devices has accelerated the use of distributed learning frameworks, where data remains local whi

local-aiarxiv-cs-lg

S2P-Net: A Spectral-Spatial Polar Network for Rotation-Invariant Object Recognition in Low-Data Regimes

arXiv:2605.09667v1 Announce Type: cross Abstract: We present S2P-Net (Spectral-Spatial Polar Network), a compact deep learning architecture that achieves mathematically guaranteed rotation invariance

researcharxiv-cs-ai

Shaping Schema via Language Representation as the Next Frontier for LLM Intelligence Expanding

arXiv:2605.09271v1 Announce Type: new Abstract: Although natural language is the default medium for Large Language Models (LLMs), its limited expressive capacity creates a profound bottleneck for comp

applicationsarxiv-cs-ai

Topological Data Analysis Applications in Natural Language Processing: A Survey

arXiv:2411.10298v5 Announce Type: replace Abstract: The surge of data available on the Internet has driven the adoption of a wide range of computational methods for analyzing and extracting insights f

applicationsarxiv-cs-cl

Unifying Scientific Communication: Fine-Grained Correspondence Across Scientific Media

model-releasesarxiv-cs-cv

arXiv:2605.05831v2 Announce Type: replace Abstract: The communication of scientific knowledge has become increasingly multimodal, spanning text, visuals, and speech through materials such as research

Users as Annotators: LLM Preference Learning from Comparison Mode

arXiv:2510.13830v2 Announce Type: replace-cross Abstract: Pairwise preference data have played an important role in the alignment of large language models (LLMs). Each sample of such data consists of

Tutorials

Voice Biomarkers for Depression and Anxiety

arXiv:2605.09908v1 Announce Type: cross Abstract: Current approaches to detecting depression and anxiety from speech primarily rely on machine learning techniques that utilize hand-engineered paraling

tutorialsarxiv-cs-ai

Yield Curve Forecasting using Machine Learning and Econometrics: A Comparative Analysis

arXiv:2605.09842v1 Announce Type: new Abstract: While machine learning has revolutionized many fields such as natural language processing (NLP) and computer vision, its impact on time-series forecasti

applicationsarxiv-cs-ai

Agentic AI and the Industrialization of Cyber Offense: Forecast, Consequences, and Defensive Priorities for Enterprises and the Mittelstand

arXiv:2605.06713v1 Announce Type: cross Abstract: Agentic AI systems can plan, call tools, inspect code, interact with web applications, and coordinate multi-step workflows. These same capabilities ch

Am old enough to remember when @GeoffreyHinton told me I was stupid for saying that LLMs regurgitate training data. He was wrong. LLM regurg…

Am old enough to remember when @GeoffreyHinton told me I was stupid for saying that LLMs regurgitate training data. He was wrong. LLM regurgitation is now one of the best-established findings in the f

safetygary-marcus--x

Cost-Ordered Feasibility for Multi-Armed Bandits with Cost Subsidy

arXiv:2605.07171v1 Announce Type: new Abstract: The classic multi-armed bandit (MAB) problem tackles the challenge of accruing maximum reward while making decisions under uncertainty. However, in appl

safetyarxiv-cs-lg

Drawing Lines in Psychological Space: What K-means Clustering Reveals in Simulated and Real Psychometric Data

arXiv:2605.06989v1 Announce Type: cross Abstract: K-means clustering is widely used in psychological and psychometric research to identify profiles, subgroups, and potential typologies, yet its classi

researcharxiv-cs-ai

From Specification to Deployment: Empirical Evidence from a W3C VC + DID Trust Infrastructure for Autonomous Agents

arXiv:2605.06738v1 Announce Type: cross Abstract: Autonomous AI agents now transact at production scale -- 69,000 bots executing 165 million transactions across 50 million USDC in cumulative volume on

IntentGrasp: A Comprehensive Benchmark for Intent Understanding

arXiv:2605.06832v1 Announce Type: cross Abstract: Accurately understanding the intent behind speech, conversation, and writing is crucial to the development of helpful Large Language Model (LLM) assis

LLM hallucinations in the wild: Large-scale evidence from non-existent citations

arXiv:2605.07723v1 Announce Type: cross Abstract: Large language models (LLMs) are known to generate plausible but false information across a wide range of contexts, yet the real-world magnitude and c

applicationsarxiv-cs-ai

Tutorials

// LLMs Improving LLMs // Interesting progress the past of couple of weeks around self-improving AI agents. If autoresearch was interesting,…

// LLMs Improving LLMs // Interesting progress the past of couple of weeks around self-improving AI agents. If autoresearch was interesting, you will like this read. (bookmark it) We've been hand-tuni

tutorialsdair-ai--x

This seems like a critical reason to open up about AI use in academia. Scholars are using old AI models, badly, and not talking about it. Ne…

This seems like a critical reason to open up about AI use in academia. Scholars are using old AI models, badly, and not talking about it. New models hallucinate very few citations, and good agentic ha

agentsethan-mollick--x

Topic Is Not Agenda: A Citation-Community Audit of Text Embeddings

model-releasesarxiv-cs-cl

arXiv:2605.07158v1 Announce Type: cross Abstract: Vector search and retrieval-augmented generation (RAG) rest on the assumption that cosine similarity between text embeddings reflects conceptual relat

The human brain🧠 is incredibly efficient because it only activates the specific neurons needed for a thought. Modern LLMs naturally try to …

The human brain🧠 is incredibly efficient because it only activates the specific neurons needed for a thought. Modern LLMs naturally try to do this too (> 95% of neurons in feedforward layers stay sile

safetydavid-ha--x

8 May 2026

LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey

arXiv:2505.00753v5 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have sparked growing interest in building fully autonomous agents. However, fully autonomous LLM-bas

safetyarxiv-cs-cl

OPENJ: A Conceptual Framework for Open-Source Digital Human Modeling and Ergonomic Assessment in a CAD Environment

arXiv:2605.04270v1 Announce Type: cross Abstract: Industrial workplace challenges range from musculoskeletal disorders -- a leading cause of occupational injury -- to suboptimal workstation layouts, i

researcharxiv-cs-ro

Position: the Stochastic Parrot in the Coal Mine. Model Collapse is a Threat to Low-Resource Communities

arXiv:2605.04127v1 Announce Type: cross Abstract: Model collapse, the degradation in performance that arises when generative models are trained on the outputs of prior models, is an increasing concern

researcharxiv-cs-cl

S1-MMAlign: A Large-Scale, Multi-Disciplinary Dataset for Scientific Figure-Text Understanding

arXiv:2601.00264v2 Announce Type: replace Abstract: Multimodal learning has revolutionized general domain tasks, yet its application in scientific discovery is hindered by the profound semantic gap be

safetyarxiv-cs-cv

Safety Must Precede the Deployment of Open-Ended AI

arXiv:2502.04512v3 Announce Type: replace Abstract: AI advancements have been significantly driven by a combination of foundation models and curiosity-driven learning aimed at increasing capability an

TNStream: Applying Tightest Neighbors to Micro-Clusters to Define Multi-Density Clusters in Streaming Data

arXiv:2505.00359v2 Announce Type: replace Abstract: In data stream clustering, systematic theory of stream clustering algorithms remains relatively scarce. Recently, density-based methods have gained

applicationsarxiv-cs-lg

Artificial Jagged Intelligence as Uneven Optimization Energy Allocation Capability Concentration, Redistribution, and Optimization Governance

arXiv:2605.01420v1 Announce Type: new Abstract: Artificial Jagged Intelligence (AJI) denotes a recurring pattern in which large learning systems exhibit strong local capabilities while remaining weak

DeRelayL: Sustainable Decentralized Relay Learning

arXiv:2605.02935v1 Announce Type: new Abstract: In the era of big data, large-scale machine learning models have revolutionized various fields, driving significant advancements. However, large-scale m

researcharxiv-cs-lg

Explainable AI for Blind and Low-Vision Users: Navigating Trust, Modality, and Interpretability in the Agentic Era

arXiv:2604.00187v2 Announce Type: replace-cross Abstract: Explainable Artificial Intelligence (XAI) is critical for ensuring trust and accountability, yet its development remains predominantly visual.

Governing What the EU AI Act Excludes: Accountability for Autonomous AI Agents in Smart City Critical Infrastructure

arXiv:2605.01091v1 Announce Type: cross Abstract: When a traffic signal controller adjusts green phases and a grid manager curtails power on the same corridor, each system may comply with its own obli

LLM-enabled Social Agents

arXiv:2605.02335v1 Announce Type: cross Abstract: Large Language Models (LLMs) have transformed agent-agent and human-agent interaction by enabling software, physical, and simulation agents to communi

Runtime Evaluation of Procedural Content Generation in an Endless Runner Game Using Autonomous Agents

arXiv:2605.01783v1 Announce Type: new Abstract: Procedural Content Generation (PCG) enables game content to be created algorithmically without direct manual level-design effort, but it introduces a se

The Productivity-Reliability Paradox: Specification-Driven Governance for AI-Augmented Software Development

arXiv:2605.01160v1 Announce Type: cross Abstract: Since 2022, AI-powered coding assistants have produced contradictory evidence: controlled studies report 20-56% productivity gains on well-scoped task

Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution

arXiv:2605.02640v1 Announce Type: new Abstract: As artificial intelligence (AI), including machine learning (ML) models and foundation models (FMs), is increasingly deployed in high-stakes domains, en

A Comprehensive Review of Fish Feeding Behavior Analysis in Aquaculture: Tasks, Techniques, and Applications

arXiv:2502.15311v3 Announce Type: replace Abstract: Fish feeding behavior analysis is a key foundation for intelligent feeding and precision aquaculture management, and plays an important role in impr

applicationsarxiv-cs-cv

Beyond Crash: Hijacking Your Autonomous Vehicle for Fun and Profit

arXiv:2602.07249v2 Announce Type: replace-cross Abstract: Autonomous Vehicles (AVs), especially vision-based AVs, are rapidly being deployed without human operators. As AVs operate in safety-critical

safetyarxiv-cs-lg

Can Causal Discovery Algorithms Help in Generating Legal Arguments?

arXiv:2605.02318v1 Announce Type: cross Abstract: In 2011, Judea Pearl received the Turing Award, considered the Nobel Prize in Computing, for fundamental contributions to artificial intelligence thro

applicationsarxiv-cs-lg

Combining Trained Models in Reinforcement Learning

arXiv:2605.02159v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) has delivered strong results in domains such as Atari and Go, but it still suffers from high sample cost and weak tran

safetyarxiv-cs-lg

Deep learning-based pavement performance modeling using multiple distress indicators and road work history

arXiv:2605.01914v1 Announce Type: new Abstract: The deterioration of pavement is a complex and dynamic process determined by different factors including material, environment, design, and some other u

applicationsarxiv-cs-lg

EditPropBench: Measuring Factual Edit Propagation in Scientific Manuscripts

model-releasesarxiv-cs-cl

arXiv:2605.02083v1 Announce Type: new Abstract: Local factual edits in scientific manuscripts often create non-local revision obligations. If a dataset changes from 215 to 80 documents, claims such as

// HeavySkill // One of the cleaner takes on agentic harness design I've read. They argue that what actually drives agent harness performanc…

// HeavySkill // One of the cleaner takes on agentic harness design I've read. They argue that what actually drives agent harness performance is not the orchestration code. It's a single inner skill:

model-releasesdair-ai--x

How Prompts Move Language Model Behavior: Frames, Salience, and Construal as Semantic Control

arXiv:2512.12688v3 Announce Type: replace-cross Abstract: Prompt engineering is widely used to shape large language model behavior, yet it is often treated as a practical heuristic rather than as a fo

researcharxiv-cs-cl

HumanSplatHMR: Closing the Loop Between Human Mesh Recovery and Gaussian Splatting Avatar

arXiv:2605.02784v1 Announce Type: new Abstract: Accurately recovering human pose and appearance from video is an essential component of scene reconstruction, with applications to motion capture, motio

safetyarxiv-cs-cv

Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces

model-releasesarxiv-cs-cl

arXiv:2605.02801v1 Announce Type: new Abstract: As large language model (LLM) agents evolve from isolated tool users into coordinated teams, reinforcement learning (RL) must optimize not only individu

Rule Extraction in Machine Learning: Chat Incremental Pattern Constructor

arXiv:2208.00335v4 Announce Type: replace Abstract: Rule extraction is a central problem in interpretable machine learning because it seeks to convert opaque predictive behavior into human-readable sy

researcharxiv-cs-lg