Search: “models”

Understanding Overparametrization in Survival Models through Interpolation

arXiv:2512.12463v3 Announce Type: replace-cross Abstract: Classical statistical learning theory predicts a U-shaped relationship between test loss and model capacity, driven by the bias-variance trade

safetyarxiv-cs-lg

23 Apr 2026

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Efficient Autoregressive Inference for Transformer Probabilistic Models

DGX agent

arXiv:2510.09477v2 Announce Type: replace-cross Abstract: Set-based transformer models for amortized probabilistic inference and meta-learning, such as neural processes, prior-fitted networks, and tab

researcharxiv-cs-lg

22 Apr 2026

Mitigating Judgment Preference Bias in Large Language Models through Group-Based Polling

arXiv:2510.08145v2 Announce Type: replace Abstract: Large Language Models (LLMs) as automatic evaluators, commonly referred to as LLM-as-a-Judge, have also attracted growing attention. This approach p

22 Apr 2026

ORCA: An Agentic Reasoning Framework for Hallucination and Adversarial Robustness in Vision-Language Models

model-releasesarxiv-cs-ai

arXiv:2509.15435v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) exhibit strong multimodal capabilities but remain vulnerable to hallucinations from intrinsic errors and

22 Apr 2026

RDP LoRA: Geometry-Driven Identification for Parameter-Efficient Adaptation in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2604.19321v1 Announce Type: cross Abstract: Fine-tuning Large Language Models (LLMs) remains structurally uncertain despite parameter-efficient methods such as Low-Rank Adaptation (LoRA), as the

22 Apr 2026

ATLAS: Constitution-Conditioned Latent Geometry and Redistribution Across Language Models and Neural Perturbation Data

arXiv:2604.17663v1 Announce Type: cross Abstract: Constitution-conditioned post-training can be analysed as a structured perturbation of a model's learned representational geometry. We introduce ATLAS

BengaliMoralBench: A Benchmark for Auditing Moral Reasoning in Large Language Models within Bengali Language and Culture

arXiv:2511.03180v2 Announce Type: replace Abstract: As multilingual Large Language Models (LLMs) gain traction across South Asia, their alignment with local ethical norms, particularly for Bengali, sp

Class-specific diffusion models improve military object detection in a low-data domain

arXiv:2604.18076v1 Announce Type: new Abstract: Diffusion-based image synthesis has emerged as a promising source of synthetic training data for AI-based object detection and classification. In this w

DOSE: Data Selection for Multi-Modal LLMs via Off-the-Shelf Models

arXiv:2604.16979v1 Announce Type: cross Abstract: High-quality and diverse multimodal data are essential for improving vision-language models (VLMs), yet existing datasets often contain noisy, redunda

Efficient Inference for Coupled Hidden Markov Models in Continuous Time and Discrete Space

arXiv:2510.12916v2 Announce Type: replace-cross Abstract: Systems of interacting continuous-time Markov chains are a powerful model class, but inference is typically intractable in high dimensional se

researcharxiv-cs-lg

Local Ai

FM-CAC: Carbon-Aware Control for Battery-Buffered Edge AI via Time-Series Foundation Models

arXiv:2604.16448v1 Announce Type: cross Abstract: As edge AI deployments scale to billions of devices running always-on, real-time compound AI pipelines, they represent a massive and largely unmanaged

local-aiarxiv-cs-lg

Forecast Sports Outcomes under Efficient Market Hypothesis: Theoretical and Experimental Analysis of Odds-Only and Generalised Linear Models

arXiv:2604.17194v1 Announce Type: cross Abstract: Converting betting odds into accurate outcome probabilities is a fundamental challenge in order to use betting odds as a benchmark for sports forecast

HalluSAE: Detecting Hallucinations in Large Language Models via Sparse Auto-Encoders

arXiv:2604.16430v1 Announce Type: new Abstract: Large Language Models (LLMs) are powerful and widely adopted, but their practical impact is limited by the well-known hallucination phenomenon. While re

Identifying Ethical Biases in Action Recognition Models

arXiv:2604.17971v1 Announce Type: new Abstract: Human Action Recognition (HAR) models are increasingly deployed in high-stakes environments, yet their fairness across different human appearances has n

safetyarxiv-cs-cv

Inertia in Moral and Value Judgments of Large Language Models

arXiv:2408.09049v3 Announce Type: replace Abstract: Large Language Models (LLMs) behave non-deterministically, and prompting has become a common method for steering their outputs. A popular strategy i

Love this work from Aksel and the post-training team at Hugging Face! Turns out the HF ecosystem (papers, datasets, models all accessible th…

model-releasesclem-delangue--x

Love this work from Aksel and the post-training team at Hugging Face! Turns out the HF ecosystem (papers, datasets, models all accessible through CLI, skills and md files) is perfect for running SOTA

Measuring Representation Robustness in Large Language Models for Geometry

arXiv:2604.16421v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated on mathematical reasoning, yet their robustness to equivalent problem representations remains po

OmniZip: Audio-Guided Dynamic Token Compression for Fast Omnimodal Large Language Models

arXiv:2511.14582v2 Announce Type: replace Abstract: Omnimodal large language models (OmniLLMs) have attracted increasing research attention of late towards unified audio-video understanding. However,

OPSDL: On-Policy Self-Distillation for Long-Context Language Models

arXiv:2604.17535v1 Announce Type: new Abstract: Extending the effective context length of large language models (LLMs) remains a central challenge for real-world applications. While recent post-traini

Parallel Test-Time Scaling for Latent Reasoning Models

arXiv:2510.07745v4 Announce Type: replace Abstract: Parallel test-time scaling (TTS) is a pivotal approach for enhancing large language models (LLMs), typically by sampling multiple token-based chains

Tutorials

Plausibility as Commonsense Reasoning: Humans Succeed, Large Language Models Do not

arXiv:2604.04825v2 Announce Type: replace Abstract: Large language models achieve strong performance on many language tasks, yet it remains unclear whether they integrate world knowledge with syntacti

tutorialsarxiv-cs-cl

Privacy Collapse: Benign Fine-Tuning Can Break Contextual Privacy in Language Models

arXiv:2601.15220v2 Announce Type: replace Abstract: We identify a novel phenomenon in language models: benign fine-tuning of frontier models can lead to privacy collapse. We find that diverse, subtle

Program Structure-aware Language Models: Targeted Software Testing beyond Textual Semantics

arXiv:2604.17715v1 Announce Type: cross Abstract: Recent advances in large language models for test case generation have improved branch coverage via prompt-engineered mutations. However, they still l

Revisiting Change VQA in Remote Sensing with Structured and Native Multimodal Qwen Models

model-releasesarxiv-cs-cv

arXiv:2604.18429v1 Announce Type: new Abstract: Change visual question answering (Change VQA) addresses the problem of answering natural-language questions about semantic changes between bi-temporal r

S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2604.18512v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable progress in single-image understanding, yet effective reasoning across multiple images remain

Test-Time Adaptation for EEG Foundation Models: A Systematic Study under Real-World Distribution Shifts

arXiv:2604.16926v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models have shown strong potential for learning generalizable representations from large-scale neural data, yet

When Background Matters: Breaking Medical Vision Language Models by Transferable Attack

arXiv:2604.17318v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are increasingly used in clinical diagnostics, yet their robustness to adversarial attacks remains largely unexplored, pos

When Choices Become Risks: Safety Failures of Large Language Models under Multiple-Choice Constraints

arXiv:2604.16916v1 Announce Type: new Abstract: Safety alignment in large language models (LLMs) is primarily evaluated under open-ended generation, where models can mitigate risk by refusing to respo

When Seeing Overrides Knowing: Disentangling Knowledge Conflicts in Vision-Language Models

arXiv:2507.13868v2 Announce Type: replace Abstract: Vision-language models (VLMs) increasingly combine visual and textual information to perform complex tasks. However, conflicts between their interna

Local Ai

AdaVFM: Adaptive Vision Foundation Models for Edge Intelligence via LLM-Guided Execution

arXiv:2604.15622v1 Announce Type: new Abstract: Language-aligned vision foundation models (VFMs) enable versatile visual understanding for always-on contextual AI, but their deployment on edge devices

local-aiarxiv-cs-cv

FineSteer: A Unified Framework for Fine-Grained Inference-Time Steering in Large Language Models

arXiv:2604.15488v1 Announce Type: cross Abstract: Large language models (LLMs) often exhibit undesirable behaviors, such as safety violations and hallucinations. Although inference-time steering offer

safetyarxiv-cs-ai

How Hypocritical Is Your LLM judge? Listener-Speaker Asymmetries in the Pragmatic Competence of Large Language Models

arXiv:2604.15873v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly studied as repositories of linguistic knowledge. In this line of work, models are commonly evaluated both

researcharxiv-cs-cl

Improving Reasoning Capabilities in Small Models through Mixture-of-Layers Distillation with Stepwise Attention on Key Information

arXiv:2604.15701v1 Announce Type: new Abstract: The significant computational demands of large language models have increased interest in distilling reasoning abilities into smaller models via Chain-o

Applications

Tabular foundation models for in-context prediction of molecular properties

arXiv:2604.16123v1 Announce Type: new Abstract: Accurate molecular property prediction is central to drug discovery, catalysis, and process design, yet real-world applications are often limited by sma

applicationsarxiv-cs-lg

I gave two MoE models the same vibe coding challenge Qwen3.6 35B A3B (31.8GB) vs Gemma4 26B A4B (23.3GB) Stack: > Unsloth Q6_K_XL > llama.cp…

model-releasesclem-delangue--x

I gave two MoE models the same vibe coding challenge Qwen3.6 35B A3B (31.8GB) vs Gemma4 26B A4B (23.3GB) Stack: > Unsloth Q6_K_XL > llama.cpp > Model-card recommended sampling for each 4 prompts, side

19 Apr 2026

Tutorials

ICYMI from a few weeks back, we compiled our learnings around how to achieve Training-Inference Parity in MoE Models. The Fundamental Issue:…

Fireworks AI published a compilation of insights on achieving training-inference parity in Mixture of Experts (MoE) models, addressing fundamental challenges in aligning model behavior between trainin

tutorialsfireworks-ai--x

18 Apr 2026

Assessing the Performance-Efficiency Trade-off of Foundation Models in Probabilistic Electricity Price Forecasting

arXiv:2604.14739v1 Announce Type: new Abstract: Large-scale renewable energy deployment introduces pronounced volatility into the electricity system, turning grid operation into a complex stochastic o

researcharxiv-cs-lg

DharmaOCR: Specialized Small Language Models for Structured OCR that outperform Open-Source and Commercial Baselines

arXiv:2604.14314v1 Announce Type: cross Abstract: This manuscript introduces DharmaOCR Full and Lite, a pair of specialized small language models (SSLMs) for structured OCR that jointly optimize trans

Exploring the flavor structure of leptons via diffusion models

arXiv:2503.21432v2 Announce Type: replace-cross Abstract: We propose a method to explore the flavor structure of leptons using diffusion models, which are known as one of generative artificial intelli

researcharxiv-cs-lg

Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI

arXiv:2403.10559v3 Announce Type: replace Abstract: This report investigates the history and impact of Generative Models and Connected and Automated Vehicles (CAVs), two groundbreaking forces pushing

safetyarxiv-cs-lg

Prompt-Guided Image Editing with Masked Logit Nudging in Visual Autoregressive Models

model-releasesarxiv-cs-cv

arXiv:2604.14591v1 Announce Type: new Abstract: We address the problem of prompt-guided image editing in visual autoregressive models. Given a source image and a target text prompt, we aim to modify t

ProRank: Prompt Warmup via Reinforcement Learning for Small Language Models Reranking

arXiv:2506.03487v3 Announce Type: replace-cross Abstract: Reranking is fundamental to information retrieval and retrieval-augmented generation, with recent Large Language Models (LLMs) significantly a

Psychological Steering of Large Language Models

arXiv:2604.14463v1 Announce Type: new Abstract: Large language models (LLMs) emulate a consistent human-like behavior that can be shaped through activation-level interventions. This paradigm is conver

researcharxiv-cs-cl

QuantCode-Bench: A Benchmark for Evaluating the Ability of Large Language Models to Generate Executable Algorithmic Trading Strategies

arXiv:2604.15151v1 Announce Type: new Abstract: Large language models have demonstrated strong performance on general-purpose programming tasks, yet their ability to generate executable algorithmic tr

Style Amnesia: Investigating Speaking Style Degradation and Mitigation in Multi-Turn Spoken Language Models

arXiv:2512.23578v3 Announce Type: replace Abstract: In this paper, we show that when spoken language models (SLMs) are instructed to speak in a specific speaking style at the beginning of a multi-turn

researcharxiv-cs-cl

Google’s DeepMind just released new 4B and 27B MedGemma models!

Google DeepMind released MedGemma, a collection of medical vision-language foundation models based on Gemma 3 in 4B and 27B parameter sizes, demonstrating advanced medical understanding and reasoning

model-releasesr-ollama

16 Apr 2026

Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges

arXiv:2604.13602v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) and related alignment paradigms have become central to steering large language models (LLMs) and multi

16 Apr 2026

Local Ai

Simplicity Prevails: The Emergence of Generalizable AIGI Detection in Visual Foundation Models