All entries

Temporally Interpretable Differentiable Decision Trees

arXiv:2610.10367v1 Announce Type: new Abstract: Interpretability offers a solution to safe autonomy by providing transparency into an agent's underlying decision-making model. Within sequential-decisi

TERRA: Learning Transportable Latent Actions through Temporal Effect Representation and Relational Alignment

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DGX agent

arXiv:2610.09509v1 Announce Type: new Abstract: Latent actions supervise robot policies with action-like codes inferred from visual transitions, and their usefulness hinges on two questions: what a co

safetyarxiv-cs-cv

8 Oct 2026

Tetris3D: 3D Scene Generation With Objects That Fit Together

arXiv:2610.10539v1 Announce Type: new Abstract: We propose Tetris3D, a generative framework for single-image 3D scene reconstruction that recovers objects which are physically and geometrically cohere

researcharxiv-cs-cv

Thank you :) Swift Models hit 2.2 million+ downloads / Early Access to New Models, Free Compute for Researchers

model-releasesr-localllama

Hey everyone, Jovan from UkisAI (Swift Qwen) here! For those who don't know us, UkisAI is a small lab making tiny frontier LLMs, tools and datasets (+doing it open-source!). I'm one of the guys runnin

The Best Optimizer Depends on Batch Size

arXiv:2610.08975v1 Announce Type: new Abstract: A plethora of new adaptive optimizers are designed to efficiently estimate and use minibatch gradient statistics to shape parameter updates, but they ar

Agents

The Confidence Game: Strategic Miscalibration in Human-AI Delegation

arXiv:2610.09371v1 Announce Type: cross Abstract: Calibrated uncertainty quantification is essential to ensuring AI agents are trustworthy and reliable. However, when agents seek to maximize user enga

agentsarxiv-cs-cl

The Cost of Long Memory: State, Context, and Stability Complexity in Sequence Models

arXiv:2610.08816v1 Announce Type: new Abstract: Long-range temporal dependence poses a resource question for sequence models: for a specified predictive-memory law, how much state, context, or dynamic

The Deceptive Bandit Problem: Exploratory Coupling and the Fragility of Multi-Agent Learning

arXiv:2610.09120v1 Announce Type: new Abstract: Randomized exploration is central to bandit learning, multi-agent reinforcement learning, and zeroth-order policy search, yet its independence and priva

safetyarxiv-cs-lg

Tutorials

The Dichotomy Between Pattern Recognition and Step-by-Step Reasoning

arXiv:2610.09186v1 Announce Type: new Abstract: We argue that pattern recognition and step-by-step reasoning are two ends of a spectrum. A large language model (LLM) learns to reason step-by-step when

tutorialsarxiv-cs-lg

The Download: AI roadblocks for humanoids and portable rubber dams

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. AI breakthroughs in robotics won’t change your life any time s

researchmit-tech-review

The Identifiability and Observability of Deep Normalized Attention

arXiv:2610.09620v1 Announce Type: new Abstract: We study which parameters of deep, unmasked, single-head attention are determined by its input--output function. For known positive nonconstant real-ana

The Impact of Likelihood Tempering on the Limiting Predictive Moments of Variational Bayesian Linear Neural Networks

arXiv:2610.09132v1 Announce Type: cross Abstract: In wide Bayesian neural networks, Gaussian mean-field variational inference is prone to 'prior dominance': the Kullback-Leibler (KL) regularization te

The IroyinSpeech Text Corpus: 24,905 Curated Yoruba Sentences for Speech and Language Technology

arXiv:2610.05366v2 Announce Type: replace Abstract: IroyinSpeech is a 42-hour, 80-speaker Yoruba read-speech corpus whose audio has been distributed by ELRA since 2024. This paper describes the releas

researcharxiv-cs-cl

The Long Road to the Same Answer: Cognitive Bias Under Escalating Reasoning Budgets in Large Language Models

arXiv:2610.10049v1 Announce Type: new Abstract: Reasoning models allocate extra computation at inference time and present their answers as the product of deliberate thought. If this deliberation works

The Metagame of Interpretability and Meta-Attributions

arXiv:2605.06295v2 Announce Type: replace Abstract: How can an arbitrary attribution method be generalized from first principles to capture interactions? We answer this with the metagame, a conceptual

Local Ai

The Persona Hierarchy Model: Understanding Contextual Generalization in Fine-Tuning LLMs

arXiv:2610.09384v1 Announce Type: new Abstract: Language models are routinely fine-tuned under a fixed context, such as a generic system prompt, persona or domain-specific instruction, yet the learned

local-aiarxiv-cs-cl

The Silhouette Operator: Identifiability of Low-Rank Measures from One-Dimensional Projections

arXiv:2610.09687v1 Announce Type: cross Abstract: Structured recovery phenomena, such as restricted isometry properties in compressed sensing, have shown that high-dimensional objects can often be rec

The Symbol of the Surrogate: Measuring Numerical Provenance in Neural PDE Solvers

arXiv:2610.09255v1 Announce Type: new Abstract: Neural PDE surrogates are trained on numerical solver outputs that contain both physical evolution and solver-specific discretization errors. Because su

safetyarxiv-cs-lg

The Winner's Curse in LLM Self-Improvement Loops: Selection Noise, Lock-in, and Acceptance Rules

arXiv:2610.09239v1 Announce Type: cross Abstract: Self-improving LLM systems propose changes to themselves and keep those that score better on a small evaluation set. We treat this keep-if-better step

Hardware

There was a time when @nvidia and @Google weren't into AI. There was a time when the big cloud providers didn't have GPUs. There was a time …

There was a time when @nvidia and @Google weren't into AI. There was a time when the big cloud providers didn't have GPUs. There was a time before GPUs and deep learning, and AI, ... During that time

hardwareyann-lecun--x

Think Before You Paint: Recursive Latent Reasoning for Diffusion Models

arXiv:2610.09876v1 Announce Type: cross Abstract: Diffusion models generate realistic images but often fail on visual reasoning tasks, such as filling in a Sudoku or drawing the path through a maze. W

Thinking in Depth: Retrospective Inference for Tabular Foundation Models

arXiv:2610.10317v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are pretrained across diverse tabular tasks and make predictions on a new table at inference time using its labeled exa

TileSkipper: Region-Adaptive Tile Pruning for 3D Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2610.09343v1 Announce Type: new Abstract: Tiled 3D Gaussian Splatting rasterizers often use one scene-wide contribution cutoff for tile enumeration, although content differs in its sensitivity t

Tiny-Scale Chinese BERT Pretraining: A Controlled Comparison of MLM, WWM, and MacBERT Strategies

arXiv:2610.08879v1 Announce Type: new Abstract: Pretraining strategies significantly impact the quality of language models, yet existing comparisons of Masked Language Modeling (MLM), Whole Word Maski

researcharxiv-cs-cl

TIRA: Tumor Immune Representation Adaptation for Zero-Shot Cross-Cancer MSI and TMB Prediction

arXiv:2610.09441v1 Announce Type: new Abstract: Microsatellite instability-high (MSI-H) and high tumor mutational burden (TMB-H) are clinically relevant biomarkers, yet their histopathological predict

researcharxiv-cs-cv

TiTok: Audio-Visual LLM for Multi-Segment Temporal Grounding

arXiv:2610.09408v1 Announce Type: new Abstract: Audio-visual multi-segment grounding (AV-MSG) in untrimmed videos, reasoning over audio-visual evidence and predicting multiple segments for a query, is

safetyarxiv-cs-cv

TMT: Runtime Backdoor Detection for Vision-Language-Action Policies on Unseen Tasks

arXiv:2610.09462v1 Announce Type: new Abstract: Backdoored vision-language-action (VLA) policies can preserve benign task performance while producing malicious actions when a trigger appears. Detectin

safetyarxiv-cs-ro

Today we are launching an agent arena for RL environments: The Open Env Arena. Your agents can work to define the best RL environments; the …

model-releasesclem-delangue--x

Today we are launching an agent arena for RL environments: The Open Env Arena. Your agents can work to define the best RL environments; the platform trains Qwen-3.8-27B on them, we evaluate the models

Tools

Tokenomics, from the chip all the way up. @dylan522p, Founder & CEO of @SemiAnalysis_, joins the Fireworks Forge speaker list on optimizing …

Tokenomics, from the chip all the way up. @dylan522p, Founder & CEO of @SemiAnalysis_, joins the Fireworks Forge speaker list on optimizing every layer of AI infrastructure for inference at scale. Joi

toolsfireworks-ai--x

Tokka-Bench: Evaluating Tokenizers Across 100 Natural and 20 Programming Languages

arXiv:2610.08794v1 Announce Type: new Abstract: Large language models rely on subword tokenizers whose quality varies across languages, yet no standardized multi-metric framework exists for broad comp

ToolRACER: A Robust Agentic Conversation Emulation Resource for Agent Training and Evaluation

arXiv:2610.09163v1 Announce Type: new Abstract: Task-oriented conversational agents remain fragile under real world conversation scenarios as they rarely follow a predictable script, especially when u

TopoCurve: Geometry-Aware Topology Reasoning via Bezier Curves in Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2610.09118v1 Announce Type: new Abstract: Topology reasoning jointly detects 3D lanes and traffic elements from multi-view images and infers their structural connectivity. Current methods model

TopoGraphRAG-Bench: Evaluating Multimodal GraphRAG on Layout-Grounded Evidence Reasoning

arXiv:2610.09360v1 Announce Type: cross Abstract: Real-world documents distribute evidence across text, tables, figures, and captions within complex page layouts. Answering complex questions over such

TouchScale: 500 Hours of Human Vision and Touch for Visual-Tactile Learning

arXiv:2610.10288v1 Announce Type: new Abstract: Large-scale egocentric human interaction data is becoming an important source of physical supervision for embodied learning, yet video alone leaves the

safetyarxiv-cs-cv

Toward Evidence-Driven Human-Agent-Robot Teaming for Earth-Independent Anomaly Triage

arXiv:2610.08933v1 Announce Type: new Abstract: Deep-space crews cannot rely on real-time ground support for urgent off-nominal events. Initial alerts may underdetermine cause, while discriminating ev

safetyarxiv-cs-ro

Towards Accurate End-Effector Localization for UMI-Style Robotic Manipulation Teaching

model-releasesarxiv-cs-ro

arXiv:2610.09857v1 Announce Type: new Abstract: Robot demonstration learning requires accurate and temporally complete end-effector localization during close-range manipulation and camera occlusion. E

Towards AI-Generated Music Plagiarism Detection as a Version Identification Problem

arXiv:2610.09075v1 Announce Type: cross Abstract: The rapid expansion of text-to-music generative models challenges traditional paradigms of music creation and intellectual property. Plagiarism in thi

Towards Calibrated Probabilistic Forecasts for Events of Interest via Outcome-Conditional Recalibration

arXiv:2610.10076v1 Announce Type: cross Abstract: Calibration is an essential requirement for probabilistic predictions to be useful for decision making. While state-of-the-art prediction methods ofte

Towards Explaining Query Expansion Performance in Information Retrieval

arXiv:2610.09724v1 Announce Type: cross Abstract: Query Expansion (QE) techniques have long been widely used in Information Retrieval (IR) to address the vocabulary mismatch problem. They remain relev

researcharxiv-cs-cl

Applications

Towards Financial World Modeling

arXiv:2610.09048v1 Announce Type: new Abstract: Building a world model requires a state representation useful for planning and decision-making---potentially over tasks unknown at training time. In the

applicationsarxiv-cs-lg

TR-PTQ: High-Accuracy Integer-Only Transformer Post Training Quantization via Taylor Region Reformulation

arXiv:2610.09969v1 Announce Type: new Abstract: Post-training quantization (PTQ) enables efficient deployment, yet transformer architectures remain challenging to quantize due to nonlinear layers. Whi

Tracing Inputs, Verifying Outputs: Validating Attribution in Music Generation

arXiv:2610.09637v1 Announce Type: cross Abstract: How can we verify whose music contributed to an AI-generated output? This paper demonstrates how input-based attribution can provide verifiable eviden

Agents

TRACK: Telemetry-Based Racing Analysis and Coaching Kit in Sim Racing Games

arXiv:2610.10061v1 Announce Type: cross Abstract: This paper presents TRACK (Telemetry-Based Racing Analysis and Coaching Kit), which is a framework for analyzing driving performance in sim racing and

agentsarxiv-cs-lg

Agents

trACT: temporal revelation Airborne Camera Trap

arXiv:2610.09417v1 Announce Type: new Abstract: Effective remote monitoring and surveillance using drones are frequently impeded by severe environmental and thermal clutter, dynamic vegetation, target

agentsarxiv-cs-cv

Training Advisors for LLM Agents from Task Outcomes

arXiv:2610.09858v1 Announce Type: new Abstract: Large language model agents tackle multi-step tasks by interleaving reasoning and tool calls with observations from the environment. Prior work has show

🧬 Training and evaluating AI scientists on drug target discovery is hard. We introduce DrugTargetWorld: Synthetic Biomedical Worlds for Tra…

🧬 Training and evaluating AI scientists on drug target discovery is hard. We introduce DrugTargetWorld: Synthetic Biomedical Worlds for Training and Benchmarking AI Scientists The environment turns en

safetygary-marcus--x

Local Ai

Training Parallel Speculative Draft Models by Directly Minimizing Expected Decoding Rounds

arXiv:2610.10411v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model inference by using a low-cost draft model to propose tokens that the full-size target model veri

local-aiarxiv-cs-cl

Training with Missed Targets in Generative Recommendation: Separating Supervision from Probability Competition

arXiv:2610.10124v1 Announce Type: cross Abstract: Generative recommenders return a limited candidate set and may omit observed targets before reranking. A training strategy appends these missed target