arXiv AI
Aug 12
Most biomedical publications show signs of LLM-assisted writing
arXiv:2608. 10715v1 Announce Type: cross Abstract: Over the past several years, LLM-powered chatbots and agents have become widely used as a tool for academic writing.
Large language models
Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.
arXiv Machine Learning
Aug 12
Observational Policy Ranking for SMB Financial Guidance from Multi-Action Accounting Logs
arXiv:2608. 10050v1 Announce Type: new Abstract: Small and medium-sized businesses need timely financial guidance, yet historical accounting logs record self-selected and often co-occurring business changes rather than randomized recommendations.
arXiv AI
Aug 12
Rule of Thumb: Explaining Artificial Intelligence Systems using Partial Information
arXiv:2608. 10766v1 Announce Type: new Abstract: Explainable Artificial Intelligence (XAI) seeks to explain how an Artificial Intelligence (AI) system arrived at a particular decision.
arXiv AI
Aug 12
Generating Attacks for LLMs with GFlowNets
arXiv:2608. 10171v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has facilitated their ubiquitous integration into various domains, leading to widespread adoption.
arXiv AI
Aug 12
Your LLM, Your Style: Behavioral Mode Axes for LLM Behavioral Control
arXiv:2608. 10703v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly act in interactive settings where their behavioral styles affect user experience, safety, and downstream decision making.
arXiv AI
Aug 12
DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents
arXiv:2608. 10037v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly rely on external tools to accomplish complex real-world tasks, making tool documentation a critical grounding resource for LLM agents.
arXiv AI
Aug 12
Covert Visual Prompt Injection against Commercial Multimodal Large Language Models
arXiv:2603. 29418v2 Announce Type: replace-cross Abstract: Although multimodal large language models (MLLMs) are increasingly deployed in real-world applications, their instruction-following behavior leaves them vulnerable to prompt injection attacks.
arXiv Machine Learning
Aug 12
Correction and Corruption: A Two-Rate View of Error Flow in LLM Protocols
arXiv:2604. 18245v3 Announce Type: replace Abstract: Large language models operate in protocols containing multiple calls, yet added calls are usually evaluated only by their net effect.
arXiv AI
Aug 12
"YES! YES! I absolutely love this insight!" Affirmative Narration as Interactional Strategy in Dialogues with LLM Chatbots
arXiv:2607. 28646v2 Announce Type: cross Abstract: This article analyses narrative mechanisms that are common in dialogues with LLM chatbots.
arXiv Machine Learning
Aug 12
Order Matters in Retrosynthesis: Structure-aware Generation via Reaction-Center-Guided Discrete Flow Matching
arXiv:2602. 13136v2 Announce Type: replace Abstract: Template-free retrosynthesis methods treat the task as black-box sequence generation, limiting learning efficiency, while semi-template approaches rely on rigid reaction libraries that constrain generalization.
arXiv AI
Aug 12
Hybrid Token Compression for Vision-Language Models
arXiv:2512. 08240v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) rely on hundreds of visual tokens, leading to high computational and memory costs.
arXiv AI
Aug 12
Why Does CLAUDE.md Keep Growing? Catastrophic Remembering in Agentic Coding
arXiv:2608. 11095v1 Announce Type: new Abstract: Agentic coding READMEs like CLAUDE.
arXiv AI
Aug 12
Toward Human Rights Benchmarking for LLMs: A Pilot Methodology
arXiv:2608. 10268v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly mediate legal determinations over what human rights are realized, and how.
arXiv AI
Aug 12
Longitudinal Evidence That General-Purpose Chatbots Actively Foster Relational Engagement
arXiv:2608. 10672v1 Announce Type: cross Abstract: Social interaction has become one of the most common uses of LLMs, yet research on emotional bonds with AI has focused largely on how users experience these systems, leaving the systems' role in relationship formation poorly understood.
arXiv Machine Learning
Aug 12
ProbGuard: Calibrated Safety Risk Estimation from LLM Output Distributions
arXiv:2608. 10621v1 Announce Type: new Abstract: Recent research on Large Language Model (LLM) safety has widely adopted guardrails to identify unsafe LLM outputs.
arXiv AI
Aug 12
LLM Agents Factory: Retrieval of Domain-Specific LLM Agents
arXiv:2608. 09934v1 Announce Type: cross Abstract: Large language model (LLM) agents improve task performance by decomposing problems into role-specialized behaviors.
Hugging Face Trending Papers
Aug 12
Generative Video Compression Based on Hierarchical Referencing
Diffusion-based generative video compression has emerged as a promising paradigm to improve perceptual quality, where latent frames are required to be encoded efficiently while serving as denoising conditions. However, existing methods neither carefully design reference and quality structures during latent coding nor account for the impact of frame-level quality variation on denoising procedure, which limits coding efficiency and aggravates artifact propagation during generative reconstruction.
Hugging Face Trending Papers
Aug 12
CoAdapt-GUI: Joint Workflow Context and Policy Adaptation for Unseen GUI Applications
Mobile GUI agents remain brittle when deployed to applications absent from source training. We study novel-app generalization under a limited target interaction budget and without target demonstrations.
Hugging Face Trending Papers
Aug 12
Robust Multi-Tier Infant-Centered Audio Understanding with Whisper via Structured Speaker Conditioning
Recent advances in model design and self-supervised audio representations have improved speech and audio understanding, yet infant-centered naturalistic recordings remain challenging due to limited labeled data, low signal-to-noise ratio, and cross-family domain shifts. We present a family-conditioned, multi-tier audio tagger that combines a LoRA-finetuned Whisper encoder with a lightweight, target-speaker-aware Transformer for long-context inference and framewise prediction across tiers.
Hugging Face Trending Papers
Aug 12
Reinforcing Step-level Reasoning for Effective Self-Correction in LLMs
Achieving effective self-correction, where models verify and correct their own mistakes, remains a fundamental challenge for large language models (LLMs). In this work, we propose Self-Fix Step-DPO (SFS-DPO), a reinforcement learning based, two-stage framework for step-level self-verification and self-correction.