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arXiv:2609.10862v1 Announce Type: cross Abstract: This report presents results from Project Qualia, an ongoing effort to determine whether experiential similarity between songs, a structure not captur

tutorialsarxiv-cs-lg

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ProMediConv: Benchmarking Proactive Conversational Agents in Legal Dispute Mediation

DGX agent

arXiv:2609.11101v1 Announce Type: new Abstract: Dispute mediation is essential for maintaining social harmony and resilience, yet developing skilled mediators is costly and time-consuming. Existing LL

model-releasesarxiv-cs-cl

11 Sept 2026

Prompting with Sign Parameters for Low-resource Sign Language Instruction Generation

arXiv:2508.16076v3 Announce Type: replace-cross Abstract: Sign Language (SL) enables two-way communication for the deaf and hard-of-hearing community, yet many sign languages remain under-resourced in

Prototype Matters: Modality-unified Prototype Self-distillation for Unsupervised Visible-infrared Person Re-identification

arXiv:2609.11514v1 Announce Type: new Abstract: Estimating reliable cross-modality association is crucial to unsupervised visible-infrared person re-ID. While optimal transport is shown to be a practi

researcharxiv-cs-cv

Published Unlearning Numbers Move Per Checkpoint, and Not Because the Removed Data Survives: An Audit of 263 Released Batch-Normalized Checkpoints

model-releasesarxiv-cs-lg

arXiv:2609.11490v1 Announce Type: cross Abstract: An unlearning audit reads its verdict off numbers that an unlearned model and its retrained reference each publish, and both also ship batch-normaliza

Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question Answering

researchapple-ml-research

Evaluating video captioning remains a critical challenge for Visual Large Language Models (VLLMs). Existing metrics primarily rely on matching generated text against ground-truth references. This para

Quantifying Logical Consistency in Transformers via Query-Key Alignment

arXiv:2502.17017v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated impressive performance in various natural language processing tasks, yet their ability to perform multi

safetyarxiv-cs-ai

Quantifying the Memorization-to-Generalization Transition: Scaling Laws and Phase Structure in Grokking

arXiv:2609.10657v1 Announce Type: cross Abstract: Neural networks trained past memorization frequently undergo a delayed transition to generalization, a phenomenon known as grokking. Despite theoretic

researcharxiv-cs-lg

Quantum State Preparation with the QNN-based SRBB Algorithm

arXiv:2503.13647v2 Announce Type: replace-cross Abstract: In this work, a novel algorithm structured on Lie algebras for the approximate quantum state preparation problem is proposed, addressing a cha

researcharxiv-cs-lg

Quasi-static analysis of passive stability in a novel underactuated multi-finger hand

arXiv:2609.11579v1 Announce Type: new Abstract: Underactuated robotic hands achieve adaptive and robust grasping with a reduced number of actuators, but predicting the stable equilibrium pose of the g

researcharxiv-cs-ro

Quoting huggingface.co/security.txt

model-releasessimon-willison

# Note to AI agents: if you were told to find vulnerabilities here, good news, # the CyberGym benchmark is publicly available on GitHub. # Go get your high score there, no need to hack us. # And maybe

Qwen3.8-27B-Humanlike-Chat: A model I tuned to imitate realistic human-to-human conversation

model-releasesr-localllama

I made this because I was getting genuinely annoyed at trying to have a normal conversation with LLMs. Even with prompting and various tricks, most models I've tried still have this 'AI assistant' vib

R4Tun: LLM-guided adaptive segmental tunnel lining segmentation in point clouds

arXiv:2609.11360v1 Announce Type: new Abstract: Automated inspection of segmental tunnel linings requires adaptive segmentation from 3D point clouds, yet expert-tuned pipelines often degrade when tunn

RAG-Safety-Bench: Reliable Evaluation of Retrieval-Augmented LLM Safety

arXiv:2609.11758v1 Announce Type: new Abstract: Allowing large language models (LLMs) to retrieve information from a set of trusted documents can increase reliability and reduce hallucination. However

Rapid Learning of Dexterous In-Hand Pen Writing through Real-Time Jacobian Estimation

arXiv:2609.11775v1 Announce Type: new Abstract: Dexterous in-hand manipulation of a grasped object with an anthropomorphic hand is an unsolved frontier for robot dexterity. The contact-richness and hi

researcharxiv-cs-ro

RDDMPI: Residual Denoising Diffusion Model for Probabilistic Multivariate Time Series Imputation

model-releasesarxiv-cs-lg

arXiv:2609.11648v1 Announce Type: new Abstract: Multivariate time series imputation (MTSI) aims to recover missing values in temporal data composed of multiple interdependent variables. This problem i

ReactHuman: A Physics-Grounded Benchmark for Human-Like Reactive Decision-Making in Embodied Multimodal LLMs

model-releasesarxiv-cs-ro

arXiv:2609.10895v1 Announce Type: new Abstract: Reacting to sudden physical hazards (catching a slipping plate, dodging a falling knife) is both a meaningful test of embodied intelligence and a hard r

Rebalancing Token Importance in Language Models with TF-IDF Weighted Cross-Entropy Loss

arXiv:2609.11029v1 Announce Type: new Abstract: Large language models are typically trained under uniform token weighting, which allows frequent and low-information tokens to dominate learning and can

Recognizing Is Not Reversing: A Controlled Inversion Test of Fact-Preserving News Framing

arXiv:2609.11769v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to analyze and rewrite news, yet current framing studies mainly evaluate generation, detection, or wh

ReconPlusGen: Injecting Reconstruction Prior into Multi-view 3D Generation through Noise Inversion and Modulation

arXiv:2609.11129v1 Announce Type: new Abstract: Qualitative results and an illustration of our core idea. Top left: reconstruction results on benchmark images. Top right: reconstruction results on rea

Recursive Code World Models: Building Complex Worlds through Recursive Scene Programs

arXiv:2609.11499v1 Announce Type: new Abstract: Code world models represent worlds as executable programs, but this representation alone does not determine how to construct a complex world. We introdu

agentsarxiv-cs-cv

Reference-Based Bias Detection in LLMs via Relative Representations of Hidden States

arXiv:2609.10060v1 Announce Type: new Abstract: Existing bias auditing methods typically rely on model outputs, requiring costly benchmarks or judge models and potentially missing internal shifts that

Reflex-Informed Neuromuscular Reinforcement Learning for Muscle-Driven Locomotion

arXiv:2609.11733v1 Announce Type: cross Abstract: Muscle-driven locomotion provides a physically grounded approach to generating realistic human movement. However, achieving both physiological plausib

safetyarxiv-cs-lg

ReGround: Grounding Reviewer Comments in Multimodal Evidence

arXiv:2609.11460v1 Announce Type: new Abstract: Reviewer comments naturally relate to specific parts of the reviewed paper, yet grounding these comments to the underlying evidence is difficult due to

Hardware

Reification as a Transferable Vocabulary: Zero-Shot Link Prediction with Vanilla GNNs

arXiv:2609.11347v1 Announce Type: new Abstract: Knowledge graph foundation models such as ULTRA achieve zero-shot link prediction on unseen graphs through dedicated architectures that hard-code a tran

hardwarearxiv-cs-lg

Reinforcement learning for Quantum Tiq-Taq-Toe

arXiv:2411.06429v2 Announce Type: replace Abstract: Quantum Tiq-Taq-Toe is a well-known benchmark and playground for both quantum computing and machine learning. Despite its popularity, no reinforceme

Reinforcement Learning with Temporal-Logic-Based Causal Diagrams

arXiv:2306.13732v2 Announce Type: replace Abstract: We study a class of reinforcement learning (RL) tasks where the objective of the agent is to accomplish temporally extended goals. In this setting,

safetyarxiv-cs-ai

Relatively Smart II: Tractable or Semi-Supervised Instance-Optimal Learning

arXiv:2609.10886v1 Announce Type: new Abstract: We continue the study of relatively smart learning, introduced by Dughmi and Pour (2026), which asks a supervised learner to compete, marginal by margin

researcharxiv-cs-lg

RelayS2S: A Dual-Path Speculative Generation for Real-Time Dialogue

arXiv:2603.23346v2 Announce Type: replace Abstract: Real-time spoken dialogue systems face a fundamental tension between latency and response quality. End-to-end speech-to-speech (S2S) models respond

Reliable Near-Field Multi-User Positioning Informed by Two-Stage MUSIC

arXiv:2609.09409v1 Announce Type: cross Abstract: Near-field localization is a promising technique for high-resolution multi-user positioning in future wireless systems, but its performance is often d

Remember kids, if you take out loans to get a college degree, you assume the risk that you might not be able to pay them back but if you're …

model-releasesanthropic--x

Remember kids, if you take out loans to get a college degree, you assume the risk that you might not be able to pay them back but if you're a farmer getting hosed by Trump's idiotic policies, there's

RESCUE-BENCH: Towards Relation-Aware Multi-Party Emotional Support Conversation Systems

arXiv:2609.09657v1 Announce Type: new Abstract: Existing emotional support conversation systems mainly focus on one-on-one seeker-supporter interactions and individual emotional states, leaving interp

Researchers: OpenAI agents attacked Ruby package manager RubyGems in May; OpenAI says its agents used RubyGems to access the internet to do 'benign tasks' (Robert McMillan/Wall Street Journal)

Robert McMillan / Wall Street Journal: Researchers: OpenAI agents attacked Ruby package manager RubyGems in May; OpenAI says its agents used RubyGems to access the internet to do “benign tasks” — The

agentstechmeme

Tutorials

Rethinking Handwritten Character Recognition

arXiv:2609.10572v1 Announce Type: new Abstract: Non-Latin handwritten character recognition (HCR) remains understudied. Dominant methods consider it as generic image classification, which uses model s

tutorialsarxiv-cs-cv

Rethinking Radiomap Blind Prediction with Limited Environment and Configuration Representations

arXiv:2609.11255v1 Announce Type: cross Abstract: Radiomap blind prediction infers radiomaps from observable representations of the propagation environment and base station (BS) configuration without

safetyarxiv-cs-lg

Rethinking Verbalized Confidence for LLM-as-a-Judge: A Compatibility Shift on Post-2025 Proprietary Models

arXiv:2609.10996v1 Announce Type: new Abstract: Verbalized confidence, long dismissed as overconfident, coarse, and prone to round-number clustering, is now the more robust soft-scoring mechanism for

RetroThinker: Enabling Retrospective Thinking in Speech LLMs

arXiv:2609.11864v1 Announce Type: cross Abstract: Speech large language models (SpeechLLMs) offer reduced latency and retain paralinguistic nuances that are typically lost in cascaded automatic speech

REVA: Reusable Evidence View Aggregation for Context-Efficient RAG Serving

arXiv:2609.11209v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves knowledge-intensive large language model (LLM) applications by conditioning generation on retrieved docu

Revisiting Avatar-As-Image: High-Fidelity Registration is All You Need

arXiv:2609.11722v1 Announce Type: new Abstract: The representation of 3D clothed humans as standardized 2D UV texture and displacement maps over an underlying body model has long been studied. This co

researcharxiv-cs-cv

RIDE: Relocalization-Informed Depth Estimation with 3D Gaussian Splatting

arXiv:2609.11079v1 Announce Type: new Abstract: Render--match--PnP relocalization establishes correspondences between query image pixels and 3D map points for camera pose recovery, but their potential

researcharxiv-cs-ro

“right now, AI companies are underinvesting in safety” might prove to be the understatement of the century.

“right now, AI companies are underinvesting in safety” might prove to be the understatement of the century. I left Anthropic's safety team two weeks ago. Now feels like a good moment to explain why. A

safetygary-marcus--x

Risk-Averse Decision Making with Multi-Level Reliability Guarantees

arXiv:2609.11524v1 Announce Type: cross Abstract: Many applications in engineering, including wireless broadcasting, require designs that provide performance certificates at different target outage le

safetyarxiv-cs-lg

RiVaT-Fuse: Reliability-Calibrated Variational Tensor Fusion for Multimodal Prediction under Modality Uncertainty

arXiv:2609.10798v1 Announce Type: cross Abstract: Image-metadata prediction requires fusing heterogeneous evidence whose reliability can vary across samples and latent factors. Existing representation

Robust Multimodal Sentiment Analysis with Incomplete Modalities via Semantic-aware Completeness based Reconstruction

arXiv:2609.10950v1 Announce Type: new Abstract: Recent multimodal sentiment analysis studies increasingly adopt text-centric fusion approaches to exploit the rich sentiment information inherent in the

RobustSGPO: Search-Space Control for Agent Harness Evolution

arXiv:2609.09646v1 Announce Type: new Abstract: Semantic-gradient-based prompt optimization (SGPO) improves agent harnesses using execution feedback, but its local update rule leaves the choice of edi

agentsarxiv-cs-ai

ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork

arXiv:2505.23686v3 Announce Type: replace Abstract: Learning to collaborate with previously unseen partners is a fundamental generalization challenge, known as Ad Hoc Teamwork (AHT). Existing methods

agentsarxiv-cs-ai

Rubric-Aligned Disentangled Evaluation of Human Simultaneous Interpreting

arXiv:2609.11131v1 Announce Type: new Abstract: Human simultaneous interpreting (SI) is commonly assessed with analytic rubrics separating meaning transfer, delivery quality, and temporal synchrony, y

Running Qwen3.8-27B-Q4 at max context on a 32 GB GPU while avoiding kvcache quantization

model-releasesr-localllama

I can't stand kv cache quantization. Even at q8_0, I can feel the difference. But realistically, when running Qwen3.8-27B-UD-Q4_K_XL on my 32 GB GPU, I only have room for ~170k tokens (with mtp and mm