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Clueing up LLMs with Tool-Augmented Deductive Reasoning

arXiv:2609.18736v1 Announce Type: new Abstract: Despite recent advances in large language models (LLMs), performing logically consistent deductive reasoning over extended interactions remains challeng

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CoAtNet-DeepMoE: A Convolution-Attention Hybrid with DeepSeek Mixture-of-Experts for Parameter-Efficient Tomato Disease Classification

DGX agent

arXiv:2609.18038v1 Announce Type: new Abstract: The world population is growing rapidly, and technology is improving in parallel. Meeting the huge demand for food for these 7 billion people not only d

model-releasesarxiv-cs-cv

17 Sept 2026

Code Consistency Preference Optimization Verification for Language Model Alignment

model-releasesarxiv-cs-cl

arXiv:2609.19002v1 Announce Type: cross Abstract: Execution-based verification enhances large language models' mathematical reasoning through computational soundness and dependency-aware filtering. Ho

Cognitive Extensions for Dual-Process Language Agents: Memory and Self-Reflection in Interactive Environments

arXiv:2609.19128v1 Announce Type: new Abstract: Language agents remain brittle in interactive environments, where success requires long-horizon state tracking, valid action execution, and recovery fro

Colla-Q: Toward Collaborative Experts in MoE Quantization via Minimax Precision Balancing

arXiv:2609.18131v1 Announce Type: cross Abstract: In this paper, we present a Mixture-of-Experts (MoE) quantization method based on activation entropy. Although quantization reduces memory and computa

researcharxiv-cs-cl

Collaborative Memory for Multi-Agent VLM Systems

arXiv:2609.17921v1 Announce Type: new Abstract: Vision-language model (VLM) agents combine specialized perception, tools, and reasoning to address complex visual tasks. In multi-agent settings, differ

Collective Loss of Control in LLM Agent Systems: An Epidemic Account of Mutation, Contagion, and Recovery

arXiv:2609.18460v1 Announce Type: new Abstract: How does a multi-agent system evolve from a local deviation into collective loss of control? We propose an epidemic explanation organized around acciden

Tutorials

Come hang out with AI engineers, tech leads, and the Fireworks team during AI Engineer 2026. Want to leave with hands-on experience fine-tun…

Come hang out with AI engineers, tech leads, and the Fireworks team during AI Engineer 2026. Want to leave with hands-on experience fine-tuning, evaluating, and deploying a model on Fireworks? Bring y

tutorialsfireworks-ai--x

CompArt: Operationalizing Aesthetic Alignment in Text-to-Image Generation via Principles of Art

arXiv:2503.12018v2 Announce Type: replace-cross Abstract: Text-to-Image (T2I) diffusion models have made rapid progress on semantic alignment (generating what is described in the prompt), yet users st

COMPASS-ABS: Reducing Fragmentation in Shared GPU Clusters for Deep Learning Training Workloads

arXiv:2609.18519v1 Announce Type: cross Abstract: With the rapid advancement of deep learning technology, shared GPU clusters receive an increasing number of deep learning training (DLT) jobs. Yet res

safetyarxiv-cs-lg

Compiled Agency: Frontier General-Purpose Coding Agents Build Winning Game Players from Bare Interaction - from Flappy Bird to StarCraft II and Civilization

arXiv:2609.18996v1 Announce Type: new Abstract: LLM agents have repeatedly struggled to convert knowledge of a game into competent play, even when researchers build the agent around the model - supply

CompileRover: Revolutionizing Virtual Machine Compiler Optimization with a Tri-Role LLM-Driven Framework

arXiv:2609.19004v1 Announce Type: cross Abstract: Code optimization plays a crucial role in the development of virtual machine compilers, with optimization frameworks significantly enhancing the perfo

researcharxiv-cs-cl

Composite-Gradient Learning for Shared Control Authority Between Deep Reinforcement Learning and Model Predictive Control

arXiv:2609.17697v1 Announce Type: new Abstract: Integrated deep reinforcement learning (DRL) and model predictive control (MPC) methods are increasingly used to control autonomous systems by combining

agentsarxiv-cs-lg

Compositional Policy Violations: When Step-Level Compliance Fails In Agentic AI Workflows

arXiv:2609.18820v1 Announce Type: new Abstract: Agentic workflows now make consequential decisions in regulated settings, and the governance placed around them is almost entirely step-scoped: input-ou

Comprehensive reconstruction of collider events with hypergraph representation learning and graph-conditioned diffusion

arXiv:2609.18928v1 Announce Type: cross Abstract: In particle collider experiments, event reconstruction is the task of inferring the kinematics of short-lived particles produced in the hard scatter f

Local Ai

Compressive sensing inspired self-supervised single-pixel imaging

arXiv:2603.29732v2 Announce Type: replace Abstract: Single-pixel imaging (SPI) is a promising imaging modality with distinctive advantages in strongly perturbed environments. Existing SPI methods lack

local-aiarxiv-cs-cv

Confidence Comes from Experience: Experiential Confidence Estimation from Reasoning to Agents

arXiv:2609.17708v1 Announce Type: cross Abstract: Reliable confidence estimation is increasingly central to the trustworthy deployment of language models: a calibrated estimate of the probability that

Consensus-based optimization for closed-box adversarial attacks and a connection to evolution strategies

arXiv:2506.24048v2 Announce Type: replace-cross Abstract: Consensus-based optimization (CBO) has established itself as an efficient gradient-free optimization scheme, with attractive mathematical prop

Constrained PSLQ Search for Machin-like Identities Achieving Record-Low Lehmer Measures

arXiv:2508.08307v2 Announce Type: replace-cross Abstract: Machin-like arctangent relations are classical tools for computing pi, with efficiency quantified by the Lehmer measure (lambda). We present a

researcharxiv-cs-ai

Contiguity, Not Importance: Budgeted Repair of Stale KV Caches After Document Edits

arXiv:2609.17983v1 Announce Type: new Abstract: KV-cache reuse can reduce inference cost in retrieval-augmented generation and agentic systems, but cached contexts may become stale when retrieved know

Copy What Is Seen, Generate What Is Not: Training-Free Anomaly-Aware Video Restoration

arXiv:2609.18836v1 Announce Type: new Abstract: A surveillance system that detects an anomaly often has to repair the footage as well, yet the two tasks are studied in isolation: training-free anomaly

researcharxiv-cs-cv

CoRe-MARL: Cooperative Redistribution Under Unknown Dynamics Using Recurrent Multi-Agent Reinforcement Learning

arXiv:2609.18639v1 Announce Type: cross Abstract: Emergency management assistance programs, such as relief distribution, are essential for delivering necessary supplies to affected communities. Howeve

Correcting Boundary Bias and Observation Independence in Bayesian Experimental Design

arXiv:2602.01898v2 Announce Type: replace Abstract: In many experimental settings, active learning can improve sample efficiency by sequentially selecting where to measure, which is particularly valua

safetyarxiv-cs-lg

Correlation-Guided Encoder Selection for Multi-Encoder Large Audio-Language Models

model-releasesarxiv-cs-cl

arXiv:2609.18041v1 Announce Type: cross Abstract: Multi-encoder fusion extends Large Audio-Language Models (LALMs) beyond speech-centric recognition, but selecting encoders via intuition or exhaustive

CPR: Combining global composing, local performing and full-sequence refining in piano rendering with continuous autoregressive modelling

arXiv:2609.18216v1 Announce Type: cross Abstract: Prompt-conditioned piano MIDI-to-Music rendering aims to faithfully render target notes while reproducing the timbre of a reference recording. Existin

CSWAM: Better Causal Semantic Representations for Out-of-Distribution Generalization in World Action Models

arXiv:2609.18462v1 Announce Type: cross Abstract: FastWAM-style world action models enable efficient action-only inference, but generalize poorly under visual distribution shifts. Their reconstruction

researcharxiv-cs-ai

Cultural Competence in Context: A Large Language Model Passes the Turing Test in Finland

arXiv:2609.18394v1 Announce Type: new Abstract: We report the results of a Turing Test conducted in Finland in the Finnish language. Because languages and cultural contexts are unevenly represented in

researcharxiv-cs-ai

Local Ai

Current AI

One thing we realized about AI is that when you ask it a question and have a conversation, the AI may give you a real answer, but it doesn't connect you to the real community behind your question! sub

local-air-ollama

Curvature-aware Expected Free Energy as an Acquisition Function for Bayesian Optimization

model-releasesarxiv-cs-lg

arXiv:2603.26339v2 Announce Type: replace Abstract: We propose an Expected Free Energy-based acquisition function for Bayesian optimization to solve the joint learning and optimization problem, i.e.,

Cute Critters Come to the Cloud: ‘Aniimo’ Launches on GeForce NOW

model-releasesnvidia-blog

A new creature-catching adventure is ready to stream from the cloud this week. Pawprint Studio’s Aniimo arrives on GeForce NOW at launch, inviting gamers to explore the vibrant continent of Idyll acro

CzechTopic: A Benchmark for Zero-Shot Topic Localization in Historical Czech Documents

arXiv:2603.03884v2 Announce Type: replace-cross Abstract: Topic localization aims to identify spans of text that express a given topic defined by a name and description. To study this task, we introdu

DANTINOX: A Unified Framework for Multi-Paradigm Language Modeling

arXiv:2609.17535v1 Announce Type: new Abstract: Language generation research increasingly spans three paradigms: autoregressive decoding, discrete masked diffusion, and continuous flow-matching. Compa

researcharxiv-cs-cl

Dataset-Dependent Effects of Cross-Depth Aggregation and Soft-Routed Experts in EEG Foundation Model Fine-Tuning

arXiv:2609.17886v1 Announce Type: new Abstract: EEG decoding tasks can rely on different temporal dynamics and cross-channel relationships. We test whether specialized modules improve a fully fine-tun

Decentralized Optimal Equilibrium Learning Over Dynamic Networks

arXiv:2609.17601v1 Announce Type: cross Abstract: This paper studies decentralized learning of socially optimal equilibria in finite normal-form games over dynamic communication networks. Each agent o

Decodability is Not Causality: Dissociating Probe Readouts from Behavioral Drivers via SAE Decomposition

arXiv:2609.18080v1 Announce Type: new Abstract: Linear probes can decode safety-relevant concepts such as truthfulness from language-model activations, but probe accuracy may show only decodability, n

Decodable but Misrouted: Sparse Features Uncover a Readout Gap in Vision-Language Models for Harmful Meme Detection

arXiv:2609.18860v1 Announce Type: cross Abstract: When a large vision-language model misclassifies a harmful meme, the failure may reflect missing internal evidence or an inability to route represente

Decoder-Agnostic Token Merging for Vision Transformers: A Systematic Study of G2TM

arXiv:2609.18279v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved state-of-the-art performance across a range of computer vision tasks, mainly thanks to the self-attention mecha

researcharxiv-cs-cv

Decoding Extrahepatic Targeting of Lipid Nanoparticles with Interpretable Machine Learning

arXiv:2609.17721v1 Announce Type: cross Abstract: Lipid nanoparticles (LNPs) have transformed RNA medicine, yet their clinical utility remains constrained by predominant hepatic accumulation after sys

Decoupling Vision, Language, and Action for Efficient Multi-Task Robot Policies

arXiv:2609.18374v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models attach an action module to a Vision-Language Model (VLM) with billions of parameters and pay for that backbone at ev

safetyarxiv-cs-ro

Deep learning emergent spacetime from fermionic spectral functions in holography

arXiv:2609.18566v1 Announce Type: cross Abstract: We present a physics-informed machine learning framework based on Neural Ordinary Differential Equations that solves the holographic inverse problem:

deepseek v4.1 flash on together ai is leading on ttft for pre-warmed queries for agent workflows, that startup time shows up again on every …

model-releasestogether-ai--x

deepseek v4.1 flash on together ai is leading on ttft for pre-warmed queries for agent workflows, that startup time shows up again on every model turn, so shaving it down matters more as the loop gets

deepseek-v4.1-flash vs glm-5.3-flash (old subscription)

I think these models are fairly comparable in performance but which uses more compute in the old subscription model? The old subscription model is at least still working in compute usage instead of co

model-releasesr-ollama

DeformSmith: Physics Harness-Guided Hierarchical Generation of Deformable Assets for Robot Manipulation

arXiv:2609.18620v1 Announce Type: new Abstract: Creating deformable assets for robot manipulation requires jointly specifying their geometry, appearance, and physical properties. This is especially ch

agentsarxiv-cs-ro

Democratizing Clinical Tumor Whole Genome Sequencing: 18-hour End-to-end Analysis via Trillion-parameter Large Language Models Locally Deployed on Consumer-grade Hardware

model-releasesarxiv-cs-lg

arXiv:2609.17620v1 Announce Type: cross Abstract: Whole genome sequencing (WGS) is essential for precision oncology, yet its clinical adoption remains limited by prohibitive computational costs and mu

Dependency-Aware Trajectory Refinement for Efficient Multi-Turn Agent Fine-Tuning

arXiv:2609.18417v1 Announce Type: new Abstract: Multi-turn agent trajectories often contain redundant rounds (failed tool calls, parallel sub-queries, verification-only steps) that inflate both traini

agentsarxiv-cs-cl

Derivative-Free Structured Updates for Muon

arXiv:2609.17759v1 Announce Type: cross Abstract: Muon updates matrix-valued neural-network parameters by orthogonalizing a gradient-based momentum matrix. Its reliance on derivatives limits its use w

Designing Agentic AI Workflow Portfolios under Imperfect Selection and Compute Cost

arXiv:2609.18126v1 Announce Type: new Abstract: Agentic AI systems often approach the same task through multiple workflows that differ in reasoning strategy, verification structure, and compute cost.

DetAug: Obstacle-Blind Trajectory Augmentation for Zero-shot Obstacle Avoidance

model-releasesarxiv-cs-ro

arXiv:2609.18395v1 Announce Type: new Abstract: Policies for robotic manipulation are produced by training on large teleoperated datasets. These datasets typically consist of free-space trajectories,