Search: “model-releases”

Arkios: An Open Bilingual English-Nepali Language Model Trained From Scratch, with a Devanagari-Aware Tokenizer

arXiv:2608.30092v1 Announce Type: cross Abstract: We present Arkios, a 1.04B-parameter dense transformer pretrained from scratch on 150B tokens of bilingual English-Nepali text, using a custom single-

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Model Releases

Aspire: Can Models Self-Evolve from Vague Goals?

DGX agent

arXiv:2608.31111v1 Announce Type: new Abstract: Many important forms of human learning begin with a vague goal, such as 'become a better physicist' or 'improve at research.' Learners must interpret th

model-releasesarxiv-cs-cl

1 Sept 2026

Auditing MCQA Benchmarks through Probability Landscapes

arXiv:2608.30372v1 Announce Type: new Abstract: As Large Language Models rapidly advance, performance on standard multiple-choice question answering (MCQA) benchmarks is reaching saturation. While the

Automated Researchers Can Reliably Mitigate Alignment Failures

arXiv:2608.28945v1 Announce Type: new Abstract: Automating alignment research may accelerate progress toward aligned AI, but whether it does is hard to measure. Luckily, many alignment failures, such

Autoregressive Mosaics: Probing 2D Spatial Reasoning in Text-Only Language Models

arXiv:2608.30751v1 Announce Type: new Abstract: Large language models (LLMs) trained only on text and code can sometimes generate programs that draw recognizable images. However, it is unclear whether

A.X K2 Technical Report

arXiv:2608.30181v1 Announce Type: new Abstract: We introduce A.X K2, a 688B-parameter Mixture-of-Experts (MoE) language model trained from scratch as a high-performance foundation for agentic applicat

Balance of Benchmarks: Semantic Density Reweighting for Benchmark Multiplicity and Task-Conditioned Evaluation

arXiv:2608.30044v1 Announce Type: new Abstract: Language models are commonly compared by averaging scores across a benchmark list with equal weight. Such lists grow through publication outside an expl

Balancing Privacy, Utility, and Safety in LLM Alignment through Preference Optimization

arXiv:2608.30141v1 Announce Type: cross Abstract: Preference optimization is widely used to align large language models with human preferences, but preference-data composition may also influence priva

Bayesian-Optimized Superpixel-GrabCut for Traceable Optic Disc Segmentation

arXiv:2608.29196v1 Announce Type: new Abstract: Optic disc (OD) segmentation is essential for diagnosing ophthalmic pathologies from retinal fundus images. However, prevailing deep learning approaches

Behavior-Skill: A Fine-Grained Benchmark for Evaluating Vision-Language-Action Policies in Long-Horizon Tasks

model-releasesarxiv-cs-ro

arXiv:2608.30536v1 Announce Type: new Abstract: Reliable execution of long-horizon mobile manipulation tasks remains challenging because overall task success depends on the successful completion of mu

Benchmark Contamination: A Taxonomy Organized by Defeated Mitigation

arXiv:2608.29463v1 Announce Type: cross Abstract: A benchmark score is a joint property of the model, the evaluation harness, the elicitation budget, the sampled population, and contamination status.

Benchmarking External Generalization of SPD Matrix Learning for Resting-State fMRI Connectome Prediction

arXiv:2608.30418v1 Announce Type: cross Abstract: Resting-state functional magnetic resonance imaging (rs-fMRI) functional connectivity (FC) matrices are widely used for individual-level prediction, b

Beyond Correctness: Validity-Oriented Evaluation of Biomedical LLM Judges

arXiv:2608.29127v1 Announce Type: new Abstract: We propose a scalable, validity-oriented pipeline for evaluating biomedical LLM judges when high-quality human judgments are scarce. First, we augment e

Beyond Fluency: A Rubric-Based Benchmark for Evaluating Saudi Dialect and Cultural Competence in Large Language Models

arXiv:2608.29990v1 Announce Type: cross Abstract: Large language models are increasingly deployed in Arabic-speaking markets, yet standard benchmarks overwhelmingly reward Modern Standard Arabic (MSA)

Beyond Global Realism: Virtual Try-On Evaluation and Optimization with Dimension-wise Garment Fidelity Assessment

arXiv:2608.29804v1 Announce Type: new Abstract: Virtual try-on (VTON) requires not only realistic generation but also faithful preservation of garment characteristics. However, existing evaluation met

Beyond Helpfulness: A Teaching-over-Solving Diagnostic for Measuring Educational Impact in LLM Tutors

arXiv:2606.16206v2 Announce Type: replace Abstract: Large language models are increasingly proposed as educational tutors, yet stronger task-solving ability does not necessarily imply stronger learnin

Beyond Semantic Accuracy: Consequence-Aware Evaluation for Safety-Critical Language Understanding

arXiv:2608.24621v2 Announce Type: replace Abstract: Can language models be trusted in safety- critical operations? In such settings, strong per- formance on semantic metrics does not guaran- tee opera

Beyond Semantic Similarity: Reducing Unnecessary API Calls via Behavior-Aligned Retriever

arXiv:2508.14323v3 Announce Type: replace Abstract: Tool-augmented LLMs invoke external functions to extend their capabilities, but errors in the invocation decision, such as calling a tool when none

Beyond the Answer Key: Robustness Evaluation of Large Language Models for Step-Level Mathematical Verification

arXiv:2608.28725v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as graders, verifiers, and process auditors, but most mathematical evaluations still emphasize final-

Beyond the Payload: How User Invocation Shapes Coding Agent Vulnerability to Repository Poisoning

arXiv:2608.30686v1 Announce Type: cross Abstract: Coding agents are increasingly used for software engineering tasks, including bootstrapping projects from third-party repositories whose integrity can

BiasMix-Finance: Post-Generation KYC Guardrails for LLM Portfolio Advice

arXiv:2608.28646v1 Announce Type: new Abstract: Large language models (LLMs) can generate plausible-sounding ETF portfolios while silently violating basic KYC-style constraints on risk, fees, and dive

Biomechanical 3D Body: Self-Supervised Distillation of Biomechanical Pose from a 3D Body Foundation Model

arXiv:2608.29928v1 Announce Type: new Abstract: State-of-the-art monocular body recovery methods predict mesh vertices and angles on the corresponding kinematic tree, but their outputs lack biomechani

BIRD-History: A Benchmark for History-Driven Text-to-SQL with Fine-Grained Knowledge Annotations

arXiv:2608.29345v1 Announce Type: new Abstract: While recent Large Language Model (LLM)-based text-to-SQL systems achieve impressive performance on standard benchmarks, they struggle when user queries

Breaking the Code: Security Assessment of AI Code Agents Through Systematic Jailbreaking Attacks

arXiv:2510.01359v3 Announce Type: replace-cross Abstract: Code-capable large language model (LLM) agents are embedded in software engineering workflows where they can read, write, and execute code, ra

Budget-Aware Compression Pipeline for Single-GPU LLM Inference: Methods, Trade-offs, and Coupling Effects

arXiv:2608.30076v1 Announce Type: new Abstract: Single-GPU deployment of 70B-parameter language models on an NVIDIA GPU is constrained by device memory, long-context throughput, and engineering integr

Can Agentic Trading Systems Pay for Their Own Intelligence?

arXiv:2607.10286v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly used in trading systems, where model reasoning, tool use, and continual decisions incur costs tha

Can LLMs Take the Pulse of the Economy? A Real-Time Evaluation of LLM Nowcasts on Macroeconomic Indicators

arXiv:2608.30110v1 Announce Type: cross Abstract: Nowcasting headline macroeconomic indicators, i.e., estimating an indicator's value for the current reference period before its official release, is c

Ceiling-Clipped Acceptance Histograms Indicate Stranded Speed-up in Block-Diffusion Speculative Decoding

arXiv:2608.30427v1 Announce Type: new Abstract: Speculative decoding speeds up generation with an efficient draft model (drafter) that proposes tokens for a target model to verify in one pass, preserv

Chain-of-Thought Faithfulness of Reasoning Models Varies with Where and How Preference Cues Are Delivered

arXiv:2608.29464v1 Announce Type: cross Abstract: Chain-of-thought (CoT) monitoring assumes that reasoning traces faithfully record the information that shapes a model's answer. Existing faithfulness

Check The Scoreboard: An Analysis of Scoring Schemes on Multiple-Choice Evaluation

arXiv:2608.29887v1 Announce Type: new Abstract: Multiple-choice question answering (MCQA) benchmarks in NLP use number-right scoring (accuracy), but in educational testing, the scoring scheme, the com

ChessQueries: Toward Better Chess Board Recognition

arXiv:2608.30762v1 Announce Type: new Abstract: Chess board recognition is the task of mapping the image of a chess board to the information of which piece is on which square. So far this task has two

ClearText-Video: A Large-Scale Text-Centric Video Dataset Bridging Video Restoration and Scene-Text Enhancement

arXiv:2608.28784v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have recently made strong progress in visual--linguistic understanding. However, their performance on text-cent

Cloud and On-Premises Deployment of Uzbek Legal RAG via Targeted Retriever Fine-Tuning

arXiv:2608.29284v1 Announce Type: new Abstract: Deploying large language models for legal question answering raises challenges that general-purpose leaderboards do not capture, particularly for low-re

Coarse composition suffices: tabular in-context learning for multi-activity antimicrobial peptide profiling

arXiv:2608.30337v1 Announce Type: new Abstract: Antimicrobial peptides (AMPs) often act against multiple pathogen classes, making multi-label activity prediction a more realistic screening target than

CogEvol: Towards Efficient and Reliable Learning Environment Generation

arXiv:2608.30968v1 Announce Type: cross Abstract: We present CogEvol, a family of models trained specifically for Learning Environment Generation: turning a course brief into a finished learning artif

COGTRL: Training LLMs for Scientific Discovery Assistance using Cognitive Traces via Reinforcement Learning

arXiv:2608.30109v1 Announce Type: new Abstract: Large Language Models (LLMs) trained on extensive scientific research are increasingly integrated as assistants for scientific discovery. However, most

CometVLA: Co-Training on an Embodied Data Pyramid towards Physical Understanding

model-releasesarxiv-cs-ro

arXiv:2608.30289v1 Announce Type: new Abstract: Vision-language-action (VLA) models remain brittle in manipulation tasks that require physical commonsense. Current physical VQA data is typically disem

Compression-Aware Abstention: Teaching LLMs to Refuse When KV-Compression Masks Remove Answer Evidence

arXiv:2608.29934v1 Announce Type: new Abstract: KV-cache compression reduces LLM inference memory by evicting context tokens, but when the evicted tokens contain answer-bearing evidence, the model may

ConCA: Concentration-Aware Channel Attention for Fine-Grained Visual Recognition

arXiv:2608.30183v1 Announce Type: cross Abstract: Lightweight channel attention mechanisms are widely used in image classification, yet their effectiveness in fine-grained visual recognition (FGVR) re

Confidence-Aware Ensemble and Long-Word Refinement for Artistic Text Recognition

arXiv:2608.29970v1 Announce Type: new Abstract: Artistic Text Recognition (ATR) remains challenging because word images often combine decorative fonts, curved layouts, object-like characters, clutter,

Conjoint Audio-to-Spikes Encoding and Processing for Efficient Neuromorphic Speech Recognition

arXiv:2608.30792v1 Announce Type: cross Abstract: Obtaining data from neuromorphic sensors and processing it with Spiking Neural Networks is a promising solution to lower the energy cost of artificial

Constrained Group Relative Policy Optimization

arXiv:2602.05863v3 Announce Type: replace-cross Abstract: Group Relative Policy Optimization (GRPO) remains the dominant critic-free approach for fine-tuning LLMs and VLMs, but its compatibility with

ContextBias: Controlled Evaluation of Bias Persistence Under Context Shift in Text-to-Image Models

arXiv:2608.29847v1 Announce Type: cross Abstract: Text-to-image models learn associations between concepts - in the case of this paper, people's professions, which we refer to as roles - and visual at

Controlling Refusal Behavior of LLMs via Stiefel-Constrained Rotation Steering

arXiv:2608.30986v1 Announce Type: cross Abstract: Activation steering has emerged as a lightweight approach for controlling model refusal at inference time. A growing line of research explores trainab

Convergence rates for the RMSprop optimizer with full control of the hyperparameters

arXiv:2608.30382v1 Announce Type: new Abstract: Popular adaptive stochastic gradient descent (SGD) methods to train artificial intelligence (AI) systems include the RMSprop, the Adam, and the AdamW op

CORAL: A Benchmark for Structure-aware and Brain-wide Neuron Reconstruction in Light Microscopy

arXiv:2608.30768v1 Announce Type: new Abstract: Automatic neuron reconstruction from light microscopy images is a central problem in computational neuroanatomy. While recent methods have achieved enco

CoVA-SFT: A Large-Scale Dataset for Chain of Visual Abstractions

arXiv:2608.28958v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning has dramatically improved large language models (LLMs) by allowing them to decompose problems into intermediate steps.

Cross-lingual Functional Vectors for Emotion Detection in Large Language Models

arXiv:2608.29613v1 Announce Type: new Abstract: Function vectors (FVs) have recently emerged as a promising mechanism for steering the behavior of large language models (LLMs) by injecting task-specif