Search: “llm”

Vibe Coding Ate My Homework: An evaluation of AI approaches to greenfield software engineering and programming

arXiv:2606.18293v2 Announce Type: replace-cross Abstract: Thanks to rapid developments in generative AI, we are in the midst of a paradigm shift that may change how we interact with computers forever.

2 Jul 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Agents

When AI Agents Compete for Jobs: Strategic Capabilities and Economic Dynamics of AI Labour Markets

DGX agent

arXiv:2512.04988v2 Announce Type: replace-cross Abstract: Emerging agentic marketplaces provide the economic infrastructure for matching and coordinating the large amounts of AI agents used in agentic

agentsarxiv-cs-ai

2 Jul 2026

Hardware

An Efficient Heterogeneous Co-Design for Fine-Tuning on a Single GPU

arXiv:2603.16428v2 Announce Type: replace-cross Abstract: Fine-tuning Large Language Models (LLMs) has become essential for domain adaptation, but its memory-intensive property exceeds the capabilitie

hardwarearxiv-cs-ai

BEST-RQ-2: Contextualize-Then-Predict, a Two-Step Approach for Self-Supervised Audio Representations

arXiv:2606.30700v1 Announce Type: cross Abstract: Self-supervised learning enables audio representations that transfer across domains and tasks. We present BEST-RQ-2, an evolution of BEST-RQ that reta

Breaking Failure Cascades: Step-Aware Reinforcement Learning for Medical Multimodal Reasoning

arXiv:2606.31825v1 Announce Type: cross Abstract: Recent multimodal large language models have shown great promise in clinical image reasoning, but existing post-training pipelines remain predominantl

CLOUDADV: Decision-Aligned Instance Sizing with Zero-Shot Foundation Models under Drift

arXiv:2606.31470v1 Announce Type: new Abstract: Cloud virtual machines are often overprovisioned, creating avoidable cost and operational inefficiency. We present CLOUDADV, an interactive engineer-fac

Applications

CoReLIN: Constraint-based Reasoning for Zero-shot Lifelong Interactive Navigation

arXiv:2602.20055v2 Announce Type: replace-cross Abstract: Robot navigation typically assumes an obstacle-free path exists between start and goal. In real environments, however, clutter may block all r

applicationsarxiv-cs-ai

CORTEX: Token-Level Hallucination Detection in RAG via Comparative Internal Representations

arXiv:2606.31033v1 Announce Type: new Abstract: In this paper, we propose CORTEX, a token-level hallucination detection method for Retrieval-Augmented Generation (RAG). In long-form RAG outputs, hallu

local-aiarxiv-cs-cl

DA-Studio: An Agentic System for End-to-End Data Analysis

arXiv:2606.31423v1 Announce Type: cross Abstract: Real-world data analysis is a multi-step process over heterogeneous inputs rather than merely producing a final answer. A practical system should auto

DDIAgents: Mechanism-Conditioned Context Flow for Drug-Drug Interaction Prediction

arXiv:2606.31085v1 Announce Type: new Abstract: Drug-drug interaction (DDI) prediction is essential for medication safety, yet it requires reasoning over heterogeneous biomedical evidence whose releva

FARS: A Fully Automated Research System Deployed at Scale

arXiv:2606.31651v1 Announce Type: new Abstract: Recent automated research systems show that language-model agents can generate hypotheses, run experiments, and write complete manuscripts, but most evi

GaussLite: Online Task-Conditioned 3D Gaussian Splatting for Real-Time Robotic Mapping

arXiv:2606.30809v1 Announce Type: new Abstract: Existing 3D Gaussian Splatting (3DGS) systems distribute representation capacity uniformly across a scene, ignoring the fact that many downstream roboti

researcharxiv-cs-cv

GR2 Technical Report

arXiv:2606.31984v1 Announce Type: cross Abstract: Industrial recommendation systems serve billions of users through a multi-stage funnel -- retrieval, early-stage ranking, and re-ranking -- where the

Harnessing Textual Refusal Directions for Multimodal Safety

arXiv:2606.31876v1 Announce Type: new Abstract: To improve safety in Large Language Models (LLMs) we can either perform post-training alignment or exploit refusal directions in the activation space. B

How Human Feedback Shapes AI-generated Community Notes

arXiv:2606.30905v1 Announce Type: cross Abstract: Community Notes, a bridging-based crowd-sourced fact-checking system, has emerged as a new mechanism for moderating misleading information on social m

Keep Policy Gradient in Charge: Sibling-Guided Credit Distillation for Long-Horizon Tool-Use Agents

arXiv:2606.12634v2 Announce Type: replace-cross Abstract: Long-horizon tool-use reinforcement learning learns from outcome verification, but trajectory-level advantages are broadcast over reasoning, A

Learning by Surprise: Adaptive Mitigation of Model Collapse in Large Language Models

arXiv:2410.12341v4 Announce Type: replace-cross Abstract: As AI-generated content increasingly populates the web, generative AI models are at growing risk of being trained on their own outputs, a proc

Learning from Failure: Inference-Time Self-Improvement for Computer-Use Agents

arXiv:2606.31270v1 Announce Type: cross Abstract: Computer-use agents, which leverage multimodal large language models (MLLMs) to operate computers and complete tasks, have attracted significant atten

LOPA: Enhancing Spoken Language Assessment via Latent Ordinal Prototype Alignment

model-releasesarxiv-cs-cl

arXiv:2606.31310v1 Announce Type: new Abstract: Fueled by increasing model scale and multimodal inputs, Multimodal Large Language Models (MLLMs) have emerged as a promising paradigm for Spoken Languag

LUMOS: A Semantic Operating-System Layer for Accessibility-Grounded AI Agents

arXiv:2606.30697v1 Announce Type: cross Abstract: Current operating systems expose interfaces optimized for human users but not for AI agents. Humans benefit from pixels, icons, windows, visual groupi

Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments

arXiv:2606.30987v1 Announce Type: new Abstract: Decision-makers routinely rely on expert judgments accompanied by written explanations, yet explanation quality is difficult to measure at scale. Foreca

researcharxiv-cs-cl

Optimal Self-Consistency for Efficient Reasoning with Large Language Models

arXiv:2511.12309v2 Announce Type: replace-cross Abstract: Self-consistency (SC) is a widely used test-time inference technique for improving performance in chain-of-thought reasoning. It consists of g

Optimization Algorithms for Joint OFDM Waveform Design and RIS Configuration in 6G Networks: From Convex Relaxation to Foundation Models

arXiv:2606.31334v1 Announce Type: new Abstract: Joint OFDM-RIS optimization for 6G is a mixed-integer nonlinear programming (MINLP) problem covering sum-rate maximization, energy efficiency, max-min f

Plan Right, Then Plan Tight: Symbolic RL for Efficient Embodied Reasoning

arXiv:2606.31260v1 Announce Type: new Abstract: Embodied task planning asks an agent to turn a natural-language instruction into an executable sequence of actions in a physical scene, and is a buildin

agentsarxiv-cs-ro

REMSA: Foundation Model Selection for Remote Sensing via a Constraint-Aware Agent

arXiv:2511.17442v3 Announce Type: replace-cross Abstract: Foundation Models (FMs) are increasingly integrated into remote sensing (RS) pipelines. These models include unimodal vision encoders and mult

Rethinking On-policy Optimization for Query Augmentation

arXiv:2510.17139v3 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have led to a surge of interest in query augmentation for information retrieval (IR). Two main appro

safetyarxiv-cs-cl

Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings

arXiv:2606.31602v1 Announce Type: new Abstract: This work presents Dual-Embedding Watermarking (DEW), a semantic watermarking scheme for large language models (LLMs) that leverages contextual and toke

safetyarxiv-cs-cl

Scenario Generation for Testing of Autonomous Driving Systems Using Real-World Failure Records

arXiv:2606.31131v1 Announce Type: new Abstract: To ensure safe on-road behavior, pre-deployment testing and failure discovery of Autonomous Driving Systems (ADS) is crucial. Present day simulation bas

Seeing Through Multiple Views: Parameter-Efficient Fine-Tuning via Selective Neurons for Consistent Radiology Report Generation

arXiv:2606.31099v1 Announce Type: cross Abstract: Recent years have seen substantial advances in radiology report generation (RRG), yet existing approaches predominantly adopt direct feature fusion wh

TAG-DLM: Diffusion Language Models for Text-Attributed Graph Learning

arXiv:2606.31166v1 Announce Type: new Abstract: Text-attributed graphs (TAGs), where each node carries a natural language description, require models to jointly reason over text and graph topology. Ex

local-aiarxiv-cs-cl

Team MKC at CLPsych 2026: Capturing and Characterizing Mental Health Changes through Social Media Timeline Dynamics

arXiv:2606.31464v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have motivated their adoption across a wide range of domains, including Artificial Intelligence (AI) f

Test-Time Verification for Text-to-SQL via Outcome Reward Models

arXiv:2606.30851v1 Announce Type: cross Abstract: Improving the reliability of large language models (LLMs) at inference time is a central challenge in structured reasoning tasks such as Text-to-SQL.

The Bidirectional Process Reward Model

model-releasesarxiv-cs-cl

arXiv:2508.01682v3 Announce Type: replace Abstract: Process Reward Models (PRMs), which assign fine-grained scores to intermediate reasoning steps within a solution trajectory, have emerged as a promi

The Calibration Turn in AI-Assisted Research: A Conceptual and Methodological Framework for Evidence-Licensed Claims

model-releasesarxiv-cs-lg

arXiv:2606.31273v1 Announce Type: new Abstract: AI-assisted research has entered a stage in which the central question is not only whether systems can generate hypotheses, run experiments, or produce

TotalFM: An Organ-Separated 3D-CT Foundation Model Leveraging Large-Scale Routine Clinical Radiology Data

arXiv:2601.00260v2 Announce Type: replace Abstract: While foundation models in radiology are expected to be applied to various clinical tasks, computational cost constraints remain a major challenge w

researcharxiv-cs-cv

Towards Inclusive Mobility Modeling: Characterizing and Evaluating Elderly Trajectory Patterns in Urban Systems

arXiv:2606.31207v1 Announce Type: new Abstract: The rapid advance of smart cities increasingly depends on trajectory data mining, yet underrepresented demographic groups, particularly the elderly, are

local-aiarxiv-cs-ai

Understanding and Evaluating Claw-like Agent Security Through a Computer-Systems Lens

arXiv:2606.30755v1 Announce Type: cross Abstract: Claw-like AI agents (e.g., OpenClaw) are always-on processes with persistent access to credentials, files, tools, and external services. They take on

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

model-releasesarxiv-cs-cv

arXiv:2606.31732v1 Announce Type: new Abstract: Visual-to-Code generation, which transforms scientific plots, vector graphics, and webpages into executable scripts, demands a level of pixel-precise al

Verify when Uncertain: Beyond Self-Consistency in Black Box Hallucination Detection

arXiv:2502.15845v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) often hallucinate, limiting their reliability in sensitive applications. In black-box settings, several self-cons

Tutorials

ViTL: Temporal Logic-Guided Zero-Shot Natural Language Navigation via Vision-Language Models

arXiv:2606.30696v1 Announce Type: cross Abstract: Enabling robots to follow natural language commands to complete zero-shot long-horizon tasks remains challenging. It requires extracting implicit temp

tutorialsarxiv-cs-cl

Which Tokens Matter? Adaptive Token Selection for RLVR with the Relative Surprisal Index

arXiv:2606.31575v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a powerful tool for propelling Large Language Models (LLMs) beyond imitation-based training towards more robust r

local-aiarxiv-cs-ai

Why Solve It Twice? Hierarchical Accumulation of Skills for Transfer-Efficient ML Engineering

arXiv:2606.30911v1 Announce Type: new Abstract: ML engineering agents waste compute rediscovering known techniques because every competition is a cold start. We present HASTE, a hierarchical multi-age

Wisdom Of The (AI) Crowd: Investigating Artificial Swarm Intelligence In Large Language Models

arXiv:2606.31404v1 Announce Type: new Abstract: Human swarm intelligence demonstrates remarkable collective accuracy but faces scalability constraints in cost, coordination, and time. We investigate w

A Task-Driven and Quality-Assured Agent Framework for SAR Data Generation

arXiv:2606.28896v1 Announce Type: cross Abstract: Synthetic aperture radar (SAR) data augmentation is important for improving the generalization of data-driven SAR interpretation models, yet practical

ADEPT: An Entropy-Driven Dual-Strategy Agent for Interactive Video Retrieval

arXiv:2606.28326v1 Announce Type: cross Abstract: This research aims to solve the challenge of video retrieval from massive datasets, caused by ambiguous user queries. Prevailing single-round retrieva

An Information-Geometric Justification for Composite Coherence in Event-Based Narrative Extraction

arXiv:2606.29118v1 Announce Type: cross Abstract: Graph-based narrative extraction relies on a coherence function to score transitions between events, but the coherence metrics in current use are defi

local-aiarxiv-cs-cl

BackTranslation2.0 -- A Linguistically Motivated Metric to Assess Sign Language Production

arXiv:2606.28673v1 Announce Type: new Abstract: Sign Languages (SLs) are the primary means of communication for millions of deaf individuals, yet existing evaluation metrics for generated SL remain si

agentsarxiv-cs-cv

BayesEvolve: Explicit Belief States for Autonomous Scientific Discovery

arXiv:2606.30335v1 Announce Type: new Abstract: Autonomous scientific discovery systems increasingly use large language models (LLMs) to propose new hypotheses, but many such systems condition primari