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TaRA: Training-Aware Low-Rank Adaptation Initialization

arXiv:2609.02639v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) has become a de facto standard for parameter-efficient fine-tuning (PEFT), yet its performance is highly sensitive to initi

Task-Level Natural Language Priors as Learning Signals for Low-Resource LLM Training

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DGX agent

arXiv:2609.02244v1 Announce Type: new Abstract: Large language models (LLMs) often struggle when low-resource training data are ambiguous or incomplete. Task-level natural-language priors can provide

model-releasesarxiv-cs-ai

3 Sept 2026

TC-Next: Zero-Shot Multimodal Cyclone Forecasting

arXiv:2609.02085v1 Announce Type: cross Abstract: We present TropicalCycloneNext (TC-Next), a multimodal deep learning model that forecasts tropical cyclone track and intensity at 6-24 h leads by leve

researcharxiv-cs-cv

TempoGround: State-Aware Streaming Visual Grounding with Vision-Language Models

arXiv:2609.02359v1 Announce Type: new Abstract: Visual grounding maps language referents to spatial targets and is central to open-vocabulary perception with vision-language models. Existing methods h

researcharxiv-cs-cv

Ten Architectures, One Error: Shared Failure Modes in Hyperspectral Classification under Spatially Disjoint Evaluation

model-releasesarxiv-cs-cv

arXiv:2609.01786v1 Announce Type: new Abstract: Hyperspectral image classification still relies heavily on random pixel splits within a single scene. The Salinas dataset, randomly split, is among the

Test-Time Logit Prompting for Source-Free Missing Modality Adaptation

arXiv:2609.02039v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved remarkable performance by leveraging complementary information from large-scale image-text pairs. However, m

applicationsarxiv-cs-cv

Testing Deepseek-V4-Flash-Vision-EXP on Dual RTX6000 build

model-releasesr-localllama

Upgraded my work LLM server from DSV4-Flash-0731 to the new Vision-Exp model and did this little test for fun to see quality comparison. Test was performed in Openweb UI connected to my vLLM container

Testing orangesouth/MinimaxH3CinematicRealism and vpakarinen/better-human-motion-h3-lora 'dean winchester vs sub zero' pruned fp8 model no turbo lora 32steps

model-releasesr-stablediffusion

https://huggingface.co/orangesouth/MinimaxH3CinematicRealism/tree/main https://huggingface.co/vpakarinen/better-human-motion-h3-lora/tree/main prompt integrated_multimodal_description: dy, [Shot 1] Ph

text2ql: Multi-Target Natural Language Querying via a Language-Agnostic Intermediate Representation

arXiv:2609.02115v1 Announce Type: cross Abstract: Natural language interfaces to databases have traditionally suffered from three structural limitations: exclusive targeting of relational SQL, uncondi

researcharxiv-cs-ai

The AI model is table stakes: Enterprise data is where the battle begins

Enterprises need practical solutions when it comes to artificial intelligence implementation. As organizations look to move AI projects from proof of concept into production, navigating the challenges

applicationssiliconangle

The announcement of @nvidia's acquisition of @huggingface on the same morning that Claude, ChatGPT, and Grok are all down shows the importan…

model-releasesclem-delangue--x

The announcement of @nvidia's acquisition of @huggingface on the same morning that Claude, ChatGPT, and Grok are all down shows the importance of owning your AI. Glad we'll have such a strong open mod

The Ceiling Is in the Channel: Auditing Learner Gaps and Measurement Frontiers in Clinical Prediction

arXiv:2609.01909v1 Announce Type: new Abstract: Clinical prediction can saturate for two different reasons: a fitted learner may fail to extract available information, or the recorded variables may im

researcharxiv-cs-ai

The Diagnosis a Reporter Leaves Unspoken: Surfacing Frozen Tumor Features for Brain-Tumor MRI Reporting

model-releasesarxiv-cs-cv

arXiv:2609.02411v1 Announce Type: new Abstract: A capable brain-MRI report generator can still be, in effect, diagnostically silent. When a multi-chain chain-of-thought (CoT) reporter built on a medic

The Dynamics of Continuous Mixture Collapse in Language Models

arXiv:2609.02049v1 Announce Type: cross Abstract: LLMs latent-state reasoning methods replace discrete intermediate tokens with continuous states, such as weighted mixtures of token embeddings, to ret

researcharxiv-cs-cl

The immediate impetus for Maria Bartiromo's shocking ouster from Fox News was her disclosure of confidential information to the Trump White …

model-releasesanthropic--x

The immediate impetus for Maria Bartiromo's shocking ouster from Fox News was her disclosure of confidential information to the Trump White House, a source told CNN https://edition.cnn.com/2026/09/03/

The Implications of Linguistic Illegibility for LLM Security

arXiv:2609.02852v1 Announce Type: new Abstract: LLMs are trained to generate natural language. However, various strands of evidence indicate that an LLM's externalized linguistic outputs and mechanist

safetyarxiv-cs-lg

The LA Unified School District bars ~378,000 students from using AI tools on district-provided laptops and tablets as officials review AI's role in classrooms (Julia Szymanski/LAmag)

Julia Szymanski / LAmag: The LA Unified School District bars ~378,000 students from using AI tools on district-provided laptops and tablets as officials review AI's role in classrooms — The district h

applicationstechmeme

The Memory Trust Gap: Capability-Dependent Failures in Persistent-Memory Agents

arXiv:2609.01852v1 Announce Type: new Abstract: Persistent memory supports personalized agents, but a stale stored fact can override current authoritative evidence without warning. We study when this

The Missing Temporal Link: Temporal Context Routing for Script-Driven Audio-Video Generation

arXiv:2609.02367v1 Announce Type: cross Abstract: Joint audio-video generation models have made substantial progress in visual quality and audio-visual synchronization. However, they still provide lim

safetyarxiv-cs-cv

The Utility of LLMs in Recommender Systems Explanation Evaluation

arXiv:2609.01627v1 Announce Type: cross Abstract: Explanations play a crucial role in creating trustworthy recommender systems (RS), yet choosing a good explanation method presents challenges. Many ex

researcharxiv-cs-ai

there is “no ground-truth information about what is actually happen” because your “Open” company won’t share what it is doing, but yes we ne…

there is “no ground-truth information about what is actually happen” because your “Open” company won’t share what it is doing, but yes we need regulation to ensure transparency. on that we agree. this

safetygary-marcus--x

Thinking effort aligns between humans and reasoning models in abductive reasoning

arXiv:2609.01867v1 Announce Type: cross Abstract: A major question in cognitive modeling concerns the behavioral alignment between large language models and humans across linguistic and non-linguistic

safetyarxiv-cs-ai

Thinking in Pictures: A Systematic Benchmark for Reasoning-driven Image Generation

model-releasesarxiv-cs-cv

arXiv:2609.02864v1 Announce Type: new Abstract: Recent advancements in unified generative models (UGMs) and world simulators have achieved unprecedented results in visual perception and synthesis. How

Hardware

This is very true, and something we still try to do for all products (and even features) we launch. Find a small group of customers who we t…

hardwareharrison-chase--x

This is very true, and something we still try to do for all products (and even features) we launch. Find a small group of customers who we think will push us the most on product and then build for the

TikZilla: Scaling Text-to-TikZ with High-Quality Data and Reinforcement Learning

arXiv:2603.03072v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to assist scientists across diverse workflows. A key challenge is generating high-quality figures

Today we're launching Base Labs, a research lab by Baseten. Our mandate is to make open-source as useful as possible, and our one rule is th…

Today we're launching Base Labs, a research lab by Baseten. Our mandate is to make open-source as useful as possible, and our one rule is that we publish without exception, including what fails. Up un

safetyjeremy-howard--x

ToolGate: An Executable Acceptance Pipeline for Tool-Dependent Scientific Benchmark Construction

arXiv:2609.02067v1 Announce Type: new Abstract: Scientific benchmarks are commonly built by domain experts who write tasks and cross-check one another's work, or who adapt existing material from textb

Toward Explainable and Policy-Aware AI for Carbon Credit Price Prediction: A Research Framework for Emerging Carbon Markets

arXiv:2609.01765v1 Announce Type: new Abstract: Carbon markets put a price on emissions, yet that price remains hard to forecast. Work in this area clusters on the EU and Chinese schemes, compresses r

safetyarxiv-cs-lg

Toward Robust LiDAR Semantic Segmentation for Real-World Deployment: Evaluation under Coarse Labels, Adverse Conditions, and Domain Shifts

model-releasesarxiv-cs-ro

arXiv:2609.02830v1 Announce Type: new Abstract: LiDAR-based semantic segmentation is a core perception module for autonomous vehicles and mobile robots. Despite the strong performance of recent state-

Toward Uncertainty-Aware and Generalizable Neural Decoding for Quantum LDPC Codes

arXiv:2510.06257v2 Announce Type: replace-cross Abstract: Quantum error correction (QEC) is essential for scalable quantum computing, yet decoding errors via conventional algorithms result in limited

researcharxiv-cs-lg

Agents

Towards a Foundational Ontology for Identifying and Resolving Contradictions in Dialogue-based Human-Robot Interactions

arXiv:2609.02364v1 Announce Type: cross Abstract: Existing Human-Robot Interaction (HRI) literature has focused on identifying and structuring errors, failures, conflicts, and knowledge issues (called

agentsarxiv-cs-ai

Towards Effective Physical Reservoir Computing with a Pneumatic Soft Robot

model-releasesarxiv-cs-ro

arXiv:2609.02157v1 Announce Type: new Abstract: Physical reservoir computing (PRC) refers to the use of a physical dynamical system as a computational resource for tasks such as state estimation and c

Towards One-for-All Robustness Across a Continuum of Threat Levels

arXiv:2609.02440v1 Announce Type: cross Abstract: Adversarially robust models often overfit to a specific attack budget, necessitating multiple specialized models for diverse and dynamic adversarial e

Towards Trustworthy Autonomous Robots: An Explainable AI-Based Decision Framework

arXiv:2609.02861v1 Announce Type: cross Abstract: Autonomous robots powered by deep learning face a fundamental auditability challenge: when incidents occur, investigators cannot reconstruct why the s

safetyarxiv-cs-ai

Agents

Towards Zero-Shot Transfer Across Embodiments For Driving VLAs

arXiv:2609.02341v1 Announce Type: new Abstract: Vision-Language-Action models (VLAs) have shown strong potential in autonomous driving by leveraging multimodal pretraining for instruction following, v

agentsarxiv-cs-cv

Trace as State: Reasoning Traces as Conditional States for Long-Context Transformers

model-releasesarxiv-cs-cl

arXiv:2609.02702v1 Announce Type: new Abstract: Transformers process information causally, but long-context reasoning may depend on task state discovered only later. We formalize this mismatch through

Train What You Deploy: Closing the MLP Reachability Gap in Low-Rank Clone Distillation

model-releasesarxiv-cs-cl

arXiv:2609.02006v1 Announce Type: cross Abstract: A compressed student has two shapes that need not agree: the weight it deploys at inference and the weight family its training can reach. We show that

Training-free hack to reduce MoE reasoning tokens by 8.5% without losing accuracy but increasing Active parameters per token in MOE (Qwen 35B A4B+)

model-releasesr-localllama

Hey everyone, Wanted to share a short paper we just published exploring a simple but surprisingly effective optimization for sparse MoE reasoning models. The problem: MoE reasoning models (especially

Training seeds and model-selection stability in recommender-system evaluation

model-releasesarxiv-cs-lg

arXiv:2609.02499v1 Announce Type: cross Abstract: Recommender-system experiments often rely on a single random training seed, assuming that run-to-run stochasticity has limited impact on evaluation co

TrajMind: Chaining Role-Specialized LoRAs for Fast-and-Slow Collective Trajectory Anomaly Diagnosis

arXiv:2609.02540v1 Announce Type: new Abstract: Diagnosing collective anomalies from urban trajectories is increasingly important for traffic governance, as it reveals what happened, who was involved,

researcharxiv-cs-lg

Transfer Safety Awareness for Cross-Modal Safety Drift in Multimodal Large Language Models

arXiv:2609.02082v1 Announce Type: cross Abstract: Visual modality enhances the capabilities of multimodal large language models (MLLMs) but also introduces a safety concern: a benign textual query may

safetyarxiv-cs-ai

Tri-Band Channel Measurement-Enabled Multi-Layer Digital Twin for Terahertz Wireless Data Centers

arXiv:2609.01699v1 Announce Type: new Abstract: The rapid growth of AI computing has driven increasing demands for flexible and high-capacity data-center interconnections. Owing to its ultra-wide band

researcharxiv-cs-lg

TriSAR: Task Coordination and Collision Avoidance for Aerial Robot Teams in Disaster Response

arXiv:2609.01731v1 Announce Type: new Abstract: Multi-Unmanned Aerial Vehicle (UAV) disaster-response systems require coordinated task assignment and local trajectory control, yet the individual and c

safetyarxiv-cs-ro

UAV Thermal Imagery for Inert Ordnance Screening: Multi Campaign Dataset Development,Object Detection, and Practical Recommendations

arXiv:2609.01738v1 Announce Type: new Abstract: Unexploded ordnance (UXO) continues to restrict civilian access, agricultural activity, infrastructure recovery, and environmental remediation in contam

researcharxiv-cs-cv

UE5M3 FP4 Block Scaling for Stable Language Model Pretraining

model-releasesarxiv-cs-lg

arXiv:2609.02846v1 Announce Type: new Abstract: Stable 4-bit floating-point (FP4) pretraining is difficult because the E2M1 payload represents only a narrow range of magnitudes. NVIDIA's Transformer E

UnCapsTSR: An Unsupervised Transformer-based Image Super-Resolution Approach for Capsule Endoscopy Images

arXiv:2609.02476v1 Announce Type: new Abstract: Wireless Capsule Endoscopy (WCE) captures and streams video while passing through a patient's Gastrointestinal (GI) tract and is used to examine its irr

applicationsarxiv-cs-cv

Local Ai

Uncertainty-Guided Adverse Weather Restoration via Gated Transformer Network

arXiv:2609.02434v1 Announce Type: new Abstract: Restoring images degraded by adverse weather remains challenging due to spatially heterogeneous degradations. Many existing weather-specific restoration

local-aiarxiv-cs-cv

Local Ai

Unfolding the Leech Lattice: Fused Multi-Shell Decoding and VRAM Layouts for 2-Bit LLM Weights

arXiv:2609.02652v1 Announce Type: new Abstract: Leech-lattice vector quantization holds the strongest reported 2-bit quality under its own evaluation protocol. Its kernel decodes one shell; we found n

local-aiarxiv-cs-lg