Search: “models”

A Statistical Perspective on Knowledge Distillation: Foundations, Classical Methods, and Large Language Model Extensions

arXiv:2609.33727v1 Announce Type: cross Abstract: Knowledge Distillation (KD) has emerged as a vital paradigm for transferring the capabilities of high-capacity models to efficient ``student'' counter

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Anytime-Valid LLM Leaderboards via Benchmark-weighted and Block-Factorized e-Processes

DGX agent

arXiv:2609.32248v1 Announce Type: new Abstract: Large language model (LLM) leaderboards compare model capabilities by ranking models according to their mean performance on fixed benchmarks. However, v

model-releasesarxiv-cs-lg

29 Sept 2026

Hardware

Approximating Softmax in Pretrained LLMs: Model Sensitivity and Kernel Acceleration

arXiv:2609.33586v1 Announce Type: new Abstract: On NVIDIA Blackwell B200, tensor-core throughput outpaces special-function exponential throughput by more than two orders of magnitude, exposing exponen

hardwarearxiv-cs-lg

Agents

BEHAVE: Functional Behavior Modeling Enables Self-Improving Agents for Hardware Design and Verification

arXiv:2609.34785v1 Announce Type: cross Abstract: Developing agents for hardware design and verification requires reliable correctness feedback. As a hardware specification may permit correct implemen

agentsarxiv-cs-lg

Beyond Calibration: Do a Typed-Decision Model's Probabilities Obey the Probability Axioms?

arXiv:2609.33209v1 Announce Type: cross Abstract: Typed-decision models such as TypeSafe's Jev answer a declared yes/no or multiple-choice question about a state with a probability instead of text, an

Distributed Hydrological Modeling in the Feature Space

arXiv:2609.32971v1 Announce Type: new Abstract: Accurate forecasting of river discharge and floods is very challenging. River dynamics are affected by storage, meteorological forcing, and flow propaga

Fading Expert Guidance: Bridging Model-Based and Learning-Based Control for Abortable Autonomous Overtaking

arXiv:2308.09456v2 Announce Type: replace Abstract: Overtaking on two-lane roads is a safety-critical decision-making problem for autonomous vehicles, since oncoming traffic may force the ego vehicle

safetyarxiv-cs-ro

FoundDSR: A Generalizable Foundation Model with Guided 2D Gaussian Splatting for Depth Super-Resolution

arXiv:2609.32323v1 Announce Type: new Abstract: We introduce FoundDSR, a generalizable foundation model for robust depth reconstruction across unseen data distributions using RGB-D pairs. FoundDSR beg

safetyarxiv-cs-cv

From Preference to Reciprocity: Decentralized Matching with Empirically Grounded LLM-agent Based Modeling

arXiv:2609.34679v1 Announce Type: new Abstract: Bipartite matching is a fundamental problem in game theory and market design. Classical approaches such as Gale--Shapley assume complete preferences and

local-aiarxiv-cs-lg

Harness Learning Enables Generalizable Test-Time Adaptation

arXiv:2609.35738v1 Announce Type: cross Abstract: A language-model agent is jointly defined by its model and its harness, the executable program that organizes model calls, tool use, and information f

Livin' on a Prior: Likelihood Score Approximation for Inverse Problems

arXiv:2609.34446v1 Announce Type: new Abstract: Generative models have found great success as data-driven methods of solving inverse problems. Two popular approaches work either by combining a pretrai

LukeNet: A lightweight CNN integrated with an XAI model for Smart acute lymphoblastic leukemia detection and management

arXiv:2609.31736v1 Announce Type: new Abstract: Acute Lymphoblastic Leukemia (ALL) patients require early, accurate detection to enable timely treatment and effective patient management. A Convolution

Applications

Medium-Term Multi-Resolution Electric Load Forecasting using Economic Data and Foundation Model

arXiv:2609.31806v1 Announce Type: new Abstract: Accurate medium-term, from a few months to a few years, electricity load forecasts are crucial for informed decision-making in power plant maintenance s

applicationsarxiv-cs-lg

Mend the Measurement Gap: Latent User Preference Modeling for Short-Form Video Recommendation

arXiv:2609.32839v1 Announce Type: cross Abstract: Recommender systems rely heavily on heterogeneous behavioral feedback to infer user preference. Although abundant, these signals are imperfect measure

Model-Informed Safe Reinforcement Learning for Bipedal Locomotion via Step-to-Step Prediction

arXiv:2609.34486v1 Announce Type: new Abstract: Humanoid robots promise versatile mobility in cluttered, human-centric environments, but real deployment demands principled safety. Classical model-base

safetyarxiv-cs-ro

OmniMoE-VL: A Sparse Vision-Language Model with Coupled Visual-Depth Routing

arXiv:2609.32780v1 Announce Type: new Abstract: Vision-language models (VLMs) increasingly use sparse mixture-of-experts (MoE) to scale language-side computation, yet visual information is typically r

local-aiarxiv-cs-cv

One-Step Generative Modeling via Unbalanced Optimal Transport

arXiv:2609.32708v1 Announce Type: cross Abstract: Drifting models enable one-step generation by amortizing distribution transport into training, but this efficiency places greater demands on the trans

OneSign: Unifying Sign Language Understanding Tasks with One Model

arXiv:2609.33090v1 Announce Type: cross Abstract: SLU encompasses a diverse set of tasks, including ISLR, CSLR, and SLT. Although these tasks share basic semantic and linguistic foundations, they are

P4Q: Co-designing Token Pruning and Quantization for Vision-Language Model Acceleration

arXiv:2609.34867v1 Announce Type: new Abstract: Vision language models have achieved strong performance across a wide range of multimodal applications, yet their substantial computational and memory c

RoboCompiler: Graph-Native Compilation of Closed-Chain Robots for Consistent Modeling, Control, and Simulation

arXiv:2609.35717v1 Announce Type: new Abstract: Robots with kinematic loops, coupled actuators, and changing contacts require consistent models of configuration, motion, force, and dynamics. Yet these

local-aiarxiv-cs-ro

TopoMamba: A Load-Support Relation-Guided Multi-Directional State-Space Model for Topology Optimization

arXiv:2609.33688v1 Announce Type: cross Abstract: Deep learning has emerged as an efficient alternative for predicting high-performance material distributions in topology optimization. Existing method

TriO: Tri-Modal Unsupervised Occupancy World Model for Anything Perception

arXiv:2609.32013v1 Announce Type: new Abstract: We present TriO, a multi-modal unsupervised world model that predicts 4D occupancy, obstacle segmentation, flow and LiDAR. In contrast to prior work, Tr

Wasserstein Convergence of ODE-Based Samplers in Decentralized Diffusion Model via Velocity Field Decomposition

arXiv:2606.15835v2 Announce Type: replace Abstract: Diffusion models have achieved impressive empirical success in generative tasks, and their convergence theory is now relatively well understood. Mot

When Text Matters: Design Principles for Visual Token Pruning in Vision-Language Model

arXiv:2609.34861v1 Announce Type: new Abstract: Visual token pruning has been widely studied as a practical approach to reducing the computational cost of large vision-language models. However, it str

Why and When Deep is Better than Shallow: Implementation-Agnostic State-Transition Model of Deep Learning

arXiv:2505.15064v5 Announce Type: replace Abstract: We ask when adding hidden layers improves generalization, in a model that keeps the layers fixed and varies only their number. A hidden layer is a s

AcoustiClaim: A Numeric Claim Benchmark with Instrument Ground Truth

model-releasesarxiv-cs-cl

arXiv:2609.30483v1 Announce Type: cross Abstract: Audio language models state numbers for acoustic quantities, and neither human opinion nor a judge model says whether such a number is true of the sig

Efficient Safety Benchmarking via Item Response Theory

model-releasesarxiv-cs-ai

arXiv:2606.20626v2 Announce Type: replace-cross Abstract: Safety benchmarks for language models are typically evaluated using static paradigms that treat all items as equally informative for all model

Equation discovery with Bayesian tree-adjoining grammars

arXiv:2609.31368v1 Announce Type: cross Abstract: Tree-Adjoining Grammars (TAGs) have recently been introduced to Nonlinear System Identification (NLSI) as a means of encoding an entire model class as

HybridInfer: Thermal-Aware Reinforcement-Learning Tier Routing for On-Device, Edge, and Cloud LLM Inference

arXiv:2609.30270v1 Announce Type: new Abstract: On-device inference with small language models keeps user data local, works offline, and incurs no per-query cost, so the on-device tier is preferred wh

Hardware

Jensen Huang says AI model distillation is 'competition'; Scott Bessent described it as 'theft' in July and threatened sanctions against overseas companies (Kai Nicol-Schwarz/CNBC)

Kai Nicol-Schwarz / CNBC: Jensen Huang says AI model distillation is “competition”; Scott Bessent described it as “theft” in July and threatened sanctions against overseas companies — Watch CNBC's ful

hardwaretechmeme

Online Learning via Learned Latent Bayesian Tracking

arXiv:2609.31559v1 Announce Type: new Abstract: Online learning in non-stationary environments requires models to adapt rapidly from streaming data under strict computational constraints. A principled

Applications

Precision at Speed: Sample-Efficient Online Model-Based Reinforcement Learning for Hydraulic Excavator Control

arXiv:2609.31025v1 Announce Type: cross Abstract: Precise, high-speed control remains challenging for robots with complex actuation dynamics. Learning directly on hardware is further constrained by th

applicationsarxiv-cs-lg

Self-Play Search Distillation for Large Language Model Reasoning

arXiv:2609.30936v1 Announce Type: new Abstract: Improving reasoning abilities in Large Language Models (LLMs) requires high-quality data that exposes difficult decisions, competing alternatives, and t

The Price of Thought: Does Test-Time Reasoning Pay in LLM Trading?

model-releasesarxiv-cs-ai

arXiv:2609.30705v1 Announce Type: new Abstract: While inference-time reasoning in large language models (LLMs) promises better decision making, its higher computational cost may not yield better econo

Gem16 - custom engine for Gemma4 12B & 26B on Blackwell 16GB GPUs

model-releasesr-localllama

It’s probably a bit niche and the models are a bit old at this point, but after reading about Ninfer a few months ago I did my own small vibe coded engine project for my 5080 Laptop GPU. Initially I t

27 Sept 2026

Qwen company already rushed out a Jev competitor. No open weights yet.

model-releasesr-localllama

EDIT: About that, I tried it out, and it's garbage so far. I did some basic tests through AIHubMix (do not use that platform btw, it's trash), and my agent did some comparison. I guess it figures, it

27 Sept 2026

A Manifold-Aware Topic Modeling Approach via Rank-Based Prototypes

arXiv:2609.29630v1 Announce Type: cross Abstract: Recent topic models leverage pretrained embeddings, but neural architectures produce latent representations without grounding in specific texts, and c

Accelerating Video Diffusion via Training-Free Trajectory Routing

arXiv:2609.30096v1 Announce Type: cross Abstract: Video diffusion is computationally expensive, as it requires executing a large model across many denoising steps. Even with step-distillation, inferen

safetyarxiv-cs-ai

Accidental discovery? or known method i'm missig? - Q's on compiling in sparse engrams and ideas swimming in my head

I set out to test portable Engrams and accidentally ended up testing compiled external memory instead. Am I onto something useful or reinventing a known idea? I've been building a small open research

local-air-localllama

BiGraph-Diffuse: A Bidirectional Diffusion Language Model with Graph-Structured Retrieval For Mental Health Counseling

arXiv:2609.29519v1 Announce Type: new Abstract: Mental health disorders affect hundreds of millions of people around the world, yet access to professional counseling remains severely limited. AI-power

CaliPPer: quantifying, predicting and improving AI model performance for binding prediction

arXiv:2606.07258v1 Announce Type: cross Abstract: Binding prediction models accelerate therapeutic antibody and TCR discovery, but their performance on new datasets is unpredictable, often leading to

Agents

Epistemic-Probabilistic Model for Guarded Multi-Agent LLM Coordination

arXiv:2609.29366v1 Announce Type: new Abstract: Multi-agent large language models (LLMs) have become ubiquitous in applied AI, yet their theoretical foundations remain surprisingly understudied. Viewe

agentsarxiv-cs-ai

JoyAI-VL-Interaction: Real-Time Vision-Language Interaction Intelligence

model-releasesarxiv-cs-ai

arXiv:2606.14777v2 Announce Type: replace-cross Abstract: Many moments in the real world do not wait for a user to ask. A fire starts on a security monitor, an expression flickers across a video call,

Modeling Load-, Velocity-, and Temperature-Dependent Transmission Errors of Cycloidal Drives for Industrial Robots Using Fourier Series

arXiv:2609.29112v1 Announce Type: new Abstract: Industrial robots are rarely used for machining tasks due to their limited path accuracy. This accuracy is mainly limited by inaccuracies in the drive t

researcharxiv-cs-ro

Online Sim-to-Real Adaptation via Closed-Loop System Modeling

arXiv:2609.28878v1 Announce Type: new Abstract: Sim-to-real transfer has made substantial progress, but can still produce controllers that remain stable and functional on hardware while suffering from

safetyarxiv-cs-ro

Qwengram-0.8B: I transferred Qwen3.8 Flash-Next’s n-gram memory into Qwen3.5-0.8B — 5.05% lower validation perplexity

model-releasesr-localllama

I’ve been experimenting with whether Qwen3.8-Flash-Next’s pretrained PLE n-gram memory can improve a much smaller Qwen3.5-0.8B model. I trained the 0.8B setup with limited resources, mostly using free

Spooftral: Can Voxtral Audio-Language Model Detect Speech Spoofing?

arXiv:2609.28713v1 Announce Type: cross Abstract: Self-supervised learning (SSL) countermeasures (CMs) have shown strong performance in recent years. However, they often show degraded performance whil

researcharxiv-cs-cl

Agents

Underwater C3-JEPA: An Object-Centric Cross-View World Model for ROV Salvage

arXiv:2609.30214v1 Announce Type: cross Abstract: We present Underwater C^{3}-JEPA (cross-view, control-conditioned, context-extended), an object-centric multi-view predictive world model for near-fie

agentsarxiv-cs-ai