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Thinking Before Thinking: Scaling Agentic Inference Through Meta-Reasoning

arXiv:2609.38147v1 Announce Type: new Abstract: As agents take on longer and more complex problems, controlling the execution becomes a task in its own right. Each step in the run brings new control c

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Thinking in Depth, Speaking Directly: Recurrent Latent Reasoning for Paralinguistically Grounded Spoken Dialogue

DGX agent

arXiv:2609.37818v1 Announce Type: cross Abstract: Empathetic spoken dialogue requires models to use both what is said and how it is said to decide how to respond. Explicit CoT can improve paralinguist

tutorialsarxiv-cs-ai

30 Sept 2026

ThinkingGuard: Decoding Implicit Hazards via Step-by-Step Risk Attribution in Multimodal Large Language Models

arXiv:2609.36562v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, their reliability is threatened by multimodal imp

safetyarxiv-cs-ai

ThinQuant: Scalable Rotation Learning for Weight and Activation Quantization of LLMs

arXiv:2609.36120v1 Announce Type: cross Abstract: Learned rotations play an important role in enabling low-bit weight and activation quantization of large language models by smoothing outliers in the

this should be fraud. certainly taxpayers shouldn’t be subsidizing Meta’s data centers.

this should be fraud. certainly taxpayers shouldn’t be subsidizing Meta’s data centers. 🦔Meta classified its AI data centers as 'experimental pilot facilities' on its tax return. That let the Nvidia c

hardwaregary-marcus--x

This story is so enraging. When you see mark zuckerberg bootlicking and bribing Trump, it’s for protection from the consequences of corrupt …

model-releasesanthropic--x

This story is so enraging. When you see mark zuckerberg bootlicking and bribing Trump, it’s for protection from the consequences of corrupt shit like this. how the American taxpayer helps back Meta's

ThuRunel: Dynamic Decoupling for Structured Advisory Dialogue

arXiv:2609.36340v1 Announce Type: new Abstract: High-stakes advisory domains such as medical aesthetics, legal consultation, and educational planning exhibit a two-phase structure. The early phase req

Time-Anchored Diffusion Language Models: Latent-Space Caching for Fast Generation

arXiv:2609.37924v1 Announce Type: cross Abstract: Recent work on anchored diffusion language models improves denoising by shaping an intermediate latent space with supervised important-token targets.

researcharxiv-cs-cl

Timelines just got shorter... AI will understand the physical 3D space better than humans by November*

model-releasesemad-mostaque--x

Timelines just got shorter... AI will understand the physical 3D space better than humans by November* Is Google so back? Their new Gemini 4 Argon understands the physical 3D world better than any oth

Industry

To make it clear, Getty Images revenue went up the last three years not down from 917m in 2023 to 981m last year with 30% EBITDA margin. T…

To make it clear, Getty Images revenue went up the last three years not down from 917m in 2023 to 981m last year with 30% EBITDA margin. Their stock photo business dropped a bit, offset by editorial a

industryemad-mostaque--x

Today we're announcing Praxis-1, an open-weight world action model that adapts to new robot embodiments with light finetuning. Video is eati…

safetycristobal-valenzuela--x

Today we're announcing Praxis-1, an open-weight world action model that adapts to new robot embodiments with light finetuning. Video is eating the world Introducing Praxis-1, an open-weight World Acti

TomoTransformer: Towards a Foundation Model for CT Reconstruction

model-releasesarxiv-cs-cv

arXiv:2609.37605v1 Announce Type: new Abstract: Supervised deep learning has advanced sparse-view tomographic reconstruction. However, conventional models, which typically map filtered back-projection

ToolFence: Fine-Grained Authorization for Secure Tool-Using LLM Agents

arXiv:2609.37196v1 Announce Type: cross Abstract: Tool-using LLM agents remain vulnerable to indirect prompt injection because trusted instructions and untrusted observations share one context, allowi

Top tech executives met with President Donald Trump on Tuesday to discuss the future of artificial intelligence amid growing concerns over A…

Top tech executives met with President Donald Trump on Tuesday to discuss the future of artificial intelligence amid growing concerns over AI models losing control. Researchers and lawmakers are calli

hardwaregary-marcus--x

TopoEmbedX: A General Framework for Representation Learning on Topological Domains

arXiv:2609.37884v1 Announce Type: new Abstract: Topological structures such as simplicial complexes, hypergraphs, and cell complexes extend standard graph models by modeling higher-order relationships

researcharxiv-cs-lg

Topological Coherence for Self-evolving Multi-agent Systems

arXiv:2609.37953v1 Announce Type: new Abstract: Complex tasks inherently couple workflow structure, agent responsibility, collaboration, and memory access: task regions delimit responsibility and tool

TORQUE: Optimizing What (not) to Quantize Before and After Rotation

arXiv:2609.36032v1 Announce Type: cross Abstract: Uniform random rotations are an effective preprocessing step for quantization: they make normalized coordinate distributions approximately Gaussian, e

Toward a Culturally Adapted Chinese Language Agent: A Wizard-of-Oz Study of Nonverbal Behavior in Chinese-German Intercultural Interaction

arXiv:2609.35150v1 Announce Type: cross Abstract: Successful intercultural communication requires more than grammatical competence. It demands sensitivity to culturally embedded social norms whose vio

agentsarxiv-cs-cl

Towards an AI Software Factory for Data Systems

arXiv:2609.36323v1 Announce Type: new Abstract: AI-assisted coding tools deliver significant acceleration of coding, but only limited impact across the end-to-end software development lifecycle (SDLC)

Towards Better Training Signal: Advantage Clipped Policy Optimization

arXiv:2609.36816v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a cornerstone for improving the reasoning capabilities of large language models (LLMs), but the need for on-polic

safetyarxiv-cs-lg

Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions

arXiv:2609.36502v1 Announce Type: cross Abstract: Past research using log data has faced the 'learning system wall,' whereby few methods exist for generalizing models of student learning across platfo

Towards Mitigating Deceptive Safety Alignment in Large Reasoning Models

arXiv:2609.36254v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) are commonly trained with reinforcement learning (RL) to improve their generation of chain-of-thought (CoT) reasoning befo

safetyarxiv-cs-ai

Local Ai

Towards Scalable Context-Aware Single-Cell Spatial Transcriptomics Prediction from Histology Images

arXiv:2609.36429v1 Announce Type: new Abstract: Predicting gene expression from H&E-stained histology images offers a scalable alternative to costly spatial transcriptomics, yet most existing methods

local-aiarxiv-cs-cv

Towards Spatial Perception for Heterogeneous Robot Collaboration in Subterranean Mining Environments

arXiv:2609.37419v1 Announce Type: new Abstract: The autonomous extraction of deep mineral deposits in abandoned underground mines is fundamentally a multi-agent integration problem. No single platform

agentsarxiv-cs-ro

TRACE: Deployable Tree-Relational Structure Enhancement for Oncology LLMs

arXiv:2609.35810v1 Announce Type: cross Abstract: Large language models are increasingly used in oncology applications, but their predictions are often weakly grounded in explicit medical structure. W

Tracing Agent Harness Behavior with NVIDIA NeMo Relay

NVIDIA NeMo Relay supplies a common observability layer that captures ordered lifecycle events and structured trajectories—ATOF event streams, ATIF step‑by‑step footprints, and OpenTelemetry spans wit

hardwarenvidia-developer

Tracing mechanisms of sycophantic agreement in language models

arXiv:2609.35822v1 Announce Type: new Abstract: Sycophantic agreement in language models refers to the tendency to overly affirm a user's stated beliefs or preferences, often at the expense of factual

safetyarxiv-cs-cl

Tracing the Evidence: Faithful Token Attribution Through Vision-Language Reasoning

arXiv:2609.37656v1 Announce Type: new Abstract: Large vision-language models (LVLMs) exhibit strong reasoning capabilities, yet the visual and textual evidence supporting the generated responses remai

researcharxiv-cs-cv

Tracing the Evolution of Oracle Bone Characters Across Three Millennia

arXiv:2609.35674v2 Announce Type: replace Abstract: Of the approximately 4,500 Oracle Bone Inscription (OBI) characters discovered from the Shang dynasty, only about 1,600 have been deciphered. Many c

researcharxiv-cs-cl

Track-and-Complete: Learning Humanoid Skills from a Single Failed Human Video

arXiv:2609.36924v1 Announce Type: cross Abstract: Learning humanoid skills from videos typically requires a successful human demonstration, which often demands custom data collection. Although failure

safetyarxiv-cs-cv

Train Ahead, Distill Back: Bootstrapping On-Policy Self-Distillation for Large Language Models

arXiv:2609.37132v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) improves large language models by letting a self-teacher with privileged information provide dense token-level superv

safetyarxiv-cs-ai

Training-Free Global Geometric Association for 4D LiDAR Panoptic Segmentation

arXiv:2512.18991v3 Announce Type: replace-cross Abstract: Dominant paradigms for 4D LiDAR panoptic segmentation are usually required to train deep neural networks with large superimposed point clouds

Training LLMs to Verbalize Evaluation Awareness

arXiv:2609.36316v1 Announce Type: cross Abstract: Evaluation awareness (EA) can cause large language models (LLMs) to behave differently during audits than in deployment, yet measuring and accounting

Trajectory-Level Mode Guidance for Controllable Diffusion-Based Multi-Robot Motion Planning

arXiv:2609.36530v1 Announce Type: new Abstract: Motion planning often admits multiple feasible solutions, making multimodal generation valuable, particularly for flexible multi-robot coordination. Dif

agentsarxiv-cs-ro

Trajectory Soup: Pushing the Compute-Scaling Frontier of LLM Mid-training via Diverse Trajectories

arXiv:2609.37169v1 Announce Type: cross Abstract: Mid-training equips pretrained large language models with specialized and reasoning capabilities, but the returns of this stage are bounded since addi

Transformers Stop Thinking Too Early, and a Tiny LoRA Fixes It

arXiv:2609.36585v1 Announce Type: new Abstract: Pretrained transformers use little of their depth to follow references in context. Thirteen base models reliably follow only 1.4-3.6 lines, and extra pr

Transolver-sigma: Joint Spectral-Physical Subspace Modeling for Neural PDE Solving

arXiv:2609.37279v1 Announce Type: new Abstract: Neural solvers offer efficient surrogates for numerical simulation of partial differential equations (PDEs). For time-dependent problems, strong one-ste

Transversal Pooling Neural Networks

arXiv:2609.36237v1 Announce Type: new Abstract: Many learning tasks require stability to small transformations while retaining sensitivity to larger ones. We introduce transversal pooling neural netwo

researcharxiv-cs-lg

Traverse: Learning When to Remember, Reset, and Redirect for Long-Horizon Web Search

arXiv:2609.37082v1 Announce Type: new Abstract: Long-horizon information-seeking agents often accumulate noisy or misleading context, causing early mistakes to persist and making recovery increasingly

agentsarxiv-cs-cl

Local Ai

Traversing the solution space of neural networks with Hessian Null Space Continuation

arXiv:2609.38081v1 Announce Type: new Abstract: On a single task, deep networks can learn many solutions, depending on their optimizer, training data, architecture, and hyperparameters. Many of these

local-aiarxiv-cs-lg

TReVS: Integrating Textual Relevance and Visual Saliency for Efficient Vision-Language Model Token Pruning

arXiv:2609.37581v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel at visual understanding and reasoning but often incur substantial inference costs due to the large number of visua

Triadic Linear Attention: Three-Dimensional Recurrent States for Long-Context Sequence Modeling

model-releasesarxiv-cs-cl

arXiv:2609.36529v1 Announce Type: cross Abstract: Recurrent neural networks (RNNs) compress the historical context into a memory state of fixed size, thus allowing for constant-time inference. The mem

Trident: Unifying Guarded Dispatch and Host Execution for PyTorch Triton Workloads

arXiv:2609.37241v1 Announce Type: new Abstract: User-written Triton kernels enable high-performance GPU computation within PyTorch, but their end-to-end latency can remain dominated by host-side orche

hardwarearxiv-cs-lg

TTMark: Pairwise Distortion-Free Watermarking Beyond Single-Token Entropy

arXiv:2609.36372v1 Announce Type: cross Abstract: Distortion-free watermarking enables reliable attribution of machine-generated text while preserving output distribution. However, existing methods op

researcharxiv-cs-cl

Two open-weights releases: Victoria (Qwen3.8-Flash-Next with 44% of experts cut, 70% Terminal-Bench 2.1, GGUF included) and Maple (a Canada-first fine-tune)

model-releasesr-localllama

We had a Dell B300 in the lab for a few weeks and used it to create two fine tunes of Qwen Flash Next. Victoria (coding and agents) Qwen3.8-Flash-Next cut down by 44% using a paper / technique called

UGO: Unified Architecture for General Multi-Object Tracking by Segmentation

arXiv:2609.37339v1 Announce Type: new Abstract: General multi-object tracking (GMOT) tracks all instances of a user-specified category from a single first-frame exemplar. Prior work relies on bounding

researcharxiv-cs-cv

UltRAG: a Universal Simple Scalable Recipe for Knowledge Graph RAG

model-releasesarxiv-cs-cl

arXiv:2603.28773v2 Announce Type: replace-cross Abstract: Large language models (LLMs) frequently generate confident yet factually incorrect content when used for language generation (a phenomenon oft

UltraMatch: Transport Path Routing for Ultra-Fast and Memory-Efficient Image Matching

arXiv:2609.36980v1 Announce Type: new Abstract: Despite recent advances in accuracy and efficiency, coarse matching remains an indispensable yet costly stage in existing semi-dense matchers due to den

researcharxiv-cs-cv