All entries

Big Brains and Changing Environments: Cause or Consequence?

arXiv:2609.15569v1 Announce Type: cross Abstract: Large brains are metabolically costly, and associations with changing environments do not imply they evolved there, as the Cognitive Buffer Hypothesis

BIG-CBF: Behavior-Imagination-Guided Control Barrier Function with Shared Uncertainty for Mobile Robot Navigation

Content type

All Blog X Post Paper YouTube Reddit GitHub

DGX agent

arXiv:2609.14343v1 Announce Type: new Abstract: Control barrier functions (CBFs) provide a mathematically grounded framework for enforcing local collision-avoidance constraints in autonomous mobile ro

model-releasesarxiv-cs-ro

15 Sept 2026

BioDCASE: Active Learning for Bioacoustics

arXiv:2609.15255v1 Announce Type: new Abstract: Ecological monitoring increasingly relies on machine learning models, whose performance depends on the quality and quantity of labelled data. However, o

researcharxiv-cs-lg

Biomedical Reference Generation Remains Unreliable across 26 Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.14988v1 Announce Type: new Abstract: Background. Large language models are increasingly used to help write biomedical text but may fabricate references to nonexistent work. How often large

Biquaternionic Space with Complex-valued Attention for Temporal Knowledge Graph Completion

arXiv:2609.14279v1 Announce Type: cross Abstract: Temporal knowledge graph embedding (TKGE) models infer missing facts in knowledge graphs that evolve over time. Many existing models use a single geom

Safety

BLInD: Learning Driver Intent as a Distribution over Future Ego Trajectories

arXiv:2609.13941v1 Announce Type: new Abstract: We present BLInD (Blind Learned Intent Distribution), a compact network that maps recent vehicle-state history (e.g. speed, curvature, indicator, and ve

safetyarxiv-cs-cv

BlueLM-GUI Technical Report: A Real-Device-Centric Flywheel for Self-Improving Mobile GUI Agents

arXiv:2609.12394v2 Announce Type: replace Abstract: Mobile GUI agents are shifting from multi-module frameworks to native models trained end-to-end, yet industrial deployment faces three persistent ga

Hardware

BOOST: Concurrent Access to Host Memory and HBM to Accelerate LLM Inference

arXiv:2609.13592v1 Announce Type: cross Abstract: GPU memory bandwidth and capacity limit throughput in large language model (LLM) inference. The GPU memory system consists of a primary tier of high-b

hardwarearxiv-cs-lg

Local Ai

Boosting Point-supervised Temporal Action Localization via Text Refinement and Alignment

arXiv:2602.01257v2 Announce Type: replace Abstract: Recently, point-supervised temporal action localization has gained significant attention for its effective balance between labeling costs and locali

local-aiarxiv-cs-cv

Tutorials

Branched Optimal Transport Amortization

arXiv:2609.15072v1 Announce Type: cross Abstract: Methods of Branched Optimal Transport (BOT) mimic the economy and efficiency of natural tree-like structures, such as those found in rivers and biolog

tutorialsarxiv-cs-ai

Breaking speed scaling in quadrupedal robots via Huygens' coupled-pendulum dynamics

arXiv:2609.13290v1 Announce Type: new Abstract: Achieving biological-level running speeds has largely been pursued through advances in control algorithms, which improve the utilization of existing har

researcharxiv-cs-ro

Bridging Control, Inference, Transport, and Thermodynamics: From Theory to Applications in Learning

arXiv:2609.15897v1 Announce Type: cross Abstract: The last decade has seen the development of powerful methods for learning complex structure from high-dimensional data. These advances have brought to

researcharxiv-cs-lg

Local Ai

Bridging Network Psychometrics and Artificial Intelligence: An Ising-Potts Model with LLM-Derived Weights

arXiv:2609.08797v2 Announce Type: replace-cross Abstract: The Potts model extends the Ising model to multinomial data. We introduce a Rater Ising-Potts model that uses agreement indicators between pai

local-aiarxiv-cs-cl

Bridging the Gap in ECG-Based Emotion Recognition: A Unified Evaluation of Deep Learning Models

model-releasesarxiv-cs-lg

arXiv:2609.15055v1 Announce Type: cross Abstract: Deep learning has led to numerous proposed architectures for Automated Emotion Recognition (AER) from electrocardiogram (ECG) data, but inconsistencie

Bridging the Modality Gap in Long-Form Clinical Audio: A Comparative Study of Lightweight and Heavyweight End-to-End SOAP Generation

arXiv:2609.14467v1 Announce Type: cross Abstract: Automating clinical documentation from long-form doctor-patient conversations remains challenging for modern audio-language models. While cascaded ASR

Bridging the Synthetic-to-Real Gap for Few-Shot Cryo-ET Classification

arXiv:2609.14097v1 Announce Type: new Abstract: Subtomogram classification in cryo-electron tomography (cryo-ET) is a challenging problem due to the scarcity of labeled examples. While cryo-ET simulat

researcharxiv-cs-cv

Bridging Thought and Action: Taming Long-Horizon Instability in Open-Source LLM Agents with a MetaTool-Enhanced ROS Framework

arXiv:2609.13335v1 Announce Type: cross Abstract: Large Language Models (LLMs) have enabled more natural human-robot interaction, but open-source models often exhibit unstable long-horizon reasoning a

BSC-Net: A Small-Branch-Sensitive Structural Continuity Network for Coronary Vessel Segmentation and Quantitative Angiographic Analysis

arXiv:2609.15400v1 Announce Type: new Abstract: Vessel segmentation in X-ray coronary angiography (XCA) is a fundamental step for quantitative coronary analysis and subsequent assessment of coronary a

researcharxiv-cs-cv

BudgetBench: A Budget-Tiered Protocol and Pilot Harness for Memory Strategy Evaluation in Local Large Language Model Agents

model-releasesarxiv-cs-cl

arXiv:2609.13149v1 Announce Type: cross Abstract: For local large language model agents, active context is a scarce resource: memory capacity, prefill latency, cache growth, and service objectives all

Tutorials

Build an AI-powered product tagging system with Amazon SageMaker serverless model customization

Manually tagging thousands of catalog products is slow and inconsistent. This walkthrough shows how to customize Qwen3-8B with supervised fine-tuning (SFT) and reinforcement learning with verifiable r

tutorialsaws-ml-blog

Building a Production Greek-English Speech Recognizer

arXiv:2609.13498v1 Announce Type: cross Abstract: We report a multi-month engineering program to build Sophea, a production bilingual Greek-English automatic speech recognition system. We evaluate the

Building Legal Reward Models for Grounding and Abstention

arXiv:2609.14739v1 Announce Type: cross Abstract: Large language models are increasingly used in high-stakes domains such as law, where systems must ground their reasoning in retrieved evidence and ab

BusMA: A Bus Communication Substrate for Multi-Agent Systems

arXiv:2609.15054v1 Announce Type: new Abstract: Multi-Agent (MA) systems are effective at solving complex tasks that demand planning, tool use, and the synthesis of evidence from multiple sources. Exi

BVB: Benchmarking Agentic Video Understanding via Programmatic Reconstruction in Blender

model-releasesarxiv-cs-cv

arXiv:2609.15478v1 Announce Type: new Abstract: Multimodal agents can create complex videos in software such as Blender by coding without relying on diffusion models. Yet video understanding benchmark

Bypass Observation: A Conceptual Design of a Non-Intrusive Layer-Wise Semantic Extraction Architecture

arXiv:2609.13807v1 Announce Type: new Abstract: Large language models reason in high-dimensional hidden-state spaces, while users observe only final outputs. We introduce Bypass Observation, a non-int

ByteShape Qwen 3.8 27B: To KL Diverge or Not to KL Diverge, Part 2: Metric Boogaloo

model-releasesr-localllama

Hey r/LocalLLaMA, We’ve released our full ShapeLearn GGUFs for Qwen 3.8 27B. Blog / Download models TL;DR 3.84 bpw (GPU-5) reaches 99.63% of BF16’s aggregate score of 8 benchmarks, being the most accu

C^2Nav: Compare Before You Commit for Zero-Shot Vision-and-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2609.15142v1 Announce Type: new Abstract: Zero-shot vision-and-language navigation in continuous environments (VLN-CE) increasingly places foundation vision-language models (VLMs) inside the nav

CAL-MOS: Bridging Layers with Adapters for Robust MOS Prediction Across Speech Foundation Models

arXiv:2609.14956v1 Announce Type: cross Abstract: Speech Quality Assessment (SQA) is essential for modern speech technologies, and recent non-intrusive SQA predictors increasingly rely on Speech Found

Calibrating Interpretability Instruments Before Trusting Their Verdicts

arXiv:2609.14754v1 Announce Type: cross Abstract: Causal claims about large language model (LLM) internals rest on measurements. Those might include a projection, a cosine, an ablation delta, or an in

Calibrating subgrid parametrizations of single-column ocean models via simulation-based inference

model-releasesarxiv-cs-lg

arXiv:2609.13242v1 Announce Type: cross Abstract: Subgrid parametrizations of vertical mixing in ocean models depend on free coefficients that cannot be measured directly and must be calibrated agains

CALICO: A Human-Centered, Codebook-Aligned System for Annotation

model-releasesarxiv-cs-cl

arXiv:2609.14726v1 Announce Type: cross Abstract: Large language models are increasingly used to scale codebook-based annotation in scientific research, but existing workflows provide limited support

Safety

Can a Neural Encoding Model Replicate an fMRI Visualization Study?

arXiv:2609.15685v1 Announce Type: cross Abstract: Most knowledge of graphical perception comes from behavioral studies. Understanding from a neural perspective is much more limited due in part to neur

safetyarxiv-cs-cv

Can AI systems have free will?

arXiv:2609.15407v1 Announce Type: new Abstract: While there has been much discussion of whether AI systems could function as moral agents or acquire sentience, there has been very little discussion of

Can Interpretation Predict Behavior on Unseen Data?

arXiv:2507.06445v4 Announce Type: replace-cross Abstract: Interpretability research often predicts model responses to targeted mechanistic interventions. But can we predict responses to unseen input d

Applications

Can Skills Learned in Games Transfer to Real-World Work?

Good Start Labs experiments show that AI training with gameplay can lead to transferable skills: a version trained on a railroad simulation outperformed peers in financial research. Inspired by Twitch

applicationslatent-space

Can We Stop Malicious AI? KILLBENCH: A Benchmark for External AI Kill Switch Feasibility

arXiv:2511.13725v5 Announce Type: replace-cross Abstract: Malicious AI causing harm to humans is not just a Hollywood fantasy. Indeed, as highly capable models such as Claude Mythos emerge and agent s

Can We Triage LLM Translation Errors in Classical Texts Without Human References? Source Novelty, GEMBA Scoring, and Budgeted Review through Pali-to-English Translation

arXiv:2609.14963v1 Announce Type: new Abstract: As large language models become capable translators of classical texts, a key challenge is deciding which outputs need expert review when no human refer

researcharxiv-cs-cl

Can We Trust the Judges? Validation of Factuality Evaluation Methods via Answer Perturbation

arXiv:2609.15561v1 Announce Type: new Abstract: Evaluating the factual correctness of large language models (LLMs) is vital for many applications. But are our evaluation tools themselves trustworthy?

researcharxiv-cs-cl

CANAL: Channel-Aware Noise Allocation for Differentially Private Feature Distillation in Medical Image Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.13271v1 Announce Type: new Abstract: Medical image segmentation needs diverse training data, but hospitals hold complementary scans they cannot share for privacy and regulatory reasons. Kno

Canaries in the Bank: Auditing User-Level Privacy in Private Evolution

arXiv:2609.13499v1 Announce Type: cross Abstract: Private Evolution (PE) generates high-fidelity synthetic data in federated settings without exposing users' raw data. It aggregates clipped user votes

Capability-Routed Visual Retrieval and Evidence Threading for Long-Context Document Question Answering

arXiv:2609.13268v1 Announce Type: new Abstract: Annual reports, diligence packs, and infographic dashboards bury numbers in page images: axes, cell grids, and footnotes that OCR pipelines flatten and

researcharxiv-cs-cv

CapGeo-Bench: Decoupling Visual Perception from Reasoning and Evaluating Geometric Understanding

arXiv:2510.09302v2 Announce Type: replace-cross Abstract: While Multimodal Large Language Models (MLLMs) have achieved remarkable success in difficult purely textual mathematical reasoning tasks, even

Local Ai

CapsuleMotion: A Lightweight Real-Time Visual Motion Predictor for Capsule Endoscopy

arXiv:2609.15367v1 Announce Type: new Abstract: Video Capsule Endoscopy (VCE) is a non-invasive medical examination that allows for the observation of the small intestine, which is otherwise difficult

local-aiarxiv-cs-cv

Carbon-Aware Routing for Function Calling in Edge-Cloud LLM Systems

arXiv:2609.13559v1 Announce Type: new Abstract: Large Language Models (LLMs) with function-calling capabilities are becoming critical for modern agentic AI systems. Nevertheless, current deployments t

Carryover Drafting: Recycling Rejected States for Speculative Decoding

arXiv:2609.14717v1 Announce Type: cross Abstract: Speculative decoding accelerates LLM inference by verifying multiple drafted tokens in parallel, allowing a single target forward pass to accept sever

CatchMonitor: a machine learning system for automated fish discard quantification

model-releasesarxiv-cs-cv

arXiv:2609.15484v1 Announce Type: new Abstract: We report on the continued development of CatchMonitor, resulting in a prototype computer vision system designed to automatically quantify discarded fis

Causal Analysis and Mitigation of Spurious Onsets in Full-Duplex Speech LLMs

arXiv:2609.13445v1 Announce Type: new Abstract: Speech-to-speech LLMs like Moshi, and its derivative PersonaPlex, can listen and speak concurrently through full-duplex generation. However, they can be

researcharxiv-cs-cl

Causal multi-modal AI for personalized chemosensitivity prediction

arXiv:2609.13567v1 Announce Type: new Abstract: Chemotherapy improves survival for some patients with breast cancer, but doctors cannot reliably predict who. Current guidelines rely on recurrence scor