Search: “model-releases”

ADABORD: a novel AdaBoost approach for ordinal classification

arXiv:2607.21003v1 Announce Type: new Abstract: Ordinal Classification (OC) deals with classification tasks where the classes follow a natural order. Despite the progress in OC, many existing approach

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Adaptive Multi-Horizon Reinforcement Learning

DGX agent

arXiv:2607.20656v1 Announce Type: cross Abstract: Effective decision-making in complex and changing environments requires balancing short-term and long-term consequences. In reinforcement learning (RL

model-releasesarxiv-cs-ai

24 Jul 2026

Agentic coding without the cloud: evaluating open-weight large language models on longitudinal data preparation tasks

arXiv:2607.21482v1 Announce Type: new Abstract: Large language models (LLMs) and agents are now widely used tools in code development, with data typically sent to third-party cloud-based models. Their

Agentic Designer: Progressive Multi-Agent Collaboration for Structure-Aware Interior Layout Generation

arXiv:2607.20866v1 Announce Type: new Abstract: Generating realistic interior furniture layouts that strictly adhere to architectural constraints (e.g., walls, doors, and windows) remains a fundamenta

AI Assistants Overassist

arXiv:2607.21306v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as tutors and thought partners, helping users reason through problems. While guidance from AI assis

AISE-Bench: A Full-Cycle Curated Benchmark for Information Seeking on Academic Knowledge Graphs

arXiv:2607.20498v1 Announce Type: new Abstract: Large language models (LLMs) augmented with tools are emerging as autonomous agents capable of using Web engine, APIs, and code to solve complex, long-h

An Analytically Trained Variational Surrogate for Quantum Phase Estimation on NISQ Hardware

arXiv:2607.20943v1 Announce Type: cross Abstract: Quantum Phase Estimation (QPE) is a foundational algorithm for molecular ground-state energy estimation, but its deep circuit requirements make direct

An LLM-Driven Workflow for Automated Process Control Strategy Generation and Tuning from Dynamic Process Models

arXiv:2607.21292v1 Announce Type: new Abstract: We present a structured large-language-model-driven workflow for automated multi-variable control design from dynamic process models. The workflow decom

AppWorld-UL: Benchmarking Diverse Agent-User Interactions for Tool-Use

arXiv:2607.20536v1 Announce Type: new Abstract: Tool-use agents that address day-to-day digital tasks such as ordering groceries must not only operate applications, but also interact with the user, e.

ArbiGraph: Arbitrarily Scalable Verifiable Task Graphs for Evaluating Context Management

arXiv:2607.20764v1 Announce Type: new Abstract: We introduce ARBIGRAPH, a benchmark generator for evaluating whether tool-assisted language agents can retain, update, compose, and discard task-relevan

Are Single-Token Sparse Autoencoder Features Causally Necessary? Layer-Depth and SAE-Family Effects

arXiv:2607.20596v1 Announce Type: cross Abstract: Sparse autoencoder (SAE) features are used to interpret and steer large language models, yet whether a feature's causal role is stable across SAE fami

AREX: Towards a Recursively Self-Improving Agent for Deep Research

arXiv:2607.21461v1 Announce Type: new Abstract: Deep research requires agents to find answers that jointly satisfy multiple constraints. Discovering such answers is costly, whereas verifying a candida

Attention Degradation, Function Token Anchoring, and the Limits of Attention-Based Intervention in Large Language Models

arXiv:2607.20524v1 Announce Type: new Abstract: Mean cross-positional attention degradation is widely reported in transformer interpretability, yet whether it causally limits contextual retrieval rema

Attribution Markets: A Fisher-Market Formulation for Fractional Credit Assignment Between Planned Tasks and Performed Actions

arXiv:2607.20694v1 Announce Type: new Abstract: Personal and organizational planning systems maintain two records that drift apart: what was planned (a task's effort budget) and what was done (a logge

Automated Synthesis and Adversarial Validation of Executable Causal Research Pipelines

arXiv:2607.21173v1 Announce Type: new Abstract: While automated research systems promise to accelerate empirical analysis, they are prone to silent failures: instances in which analysis code executes

Autonomous disproofs of the sum-product conjecture over mathbb R with GPT-5.5 Pro

arXiv:2607.20525v1 Announce Type: new Abstract: OpenAI's recent disproof of the Erdos unit distance conjecture marked a milestone for AI in mathematics. It also inspired another breakthrough: a human

Autonomous Topology Mutation: Safe Runtime Restructuring for Multi-Agent LLM Systems with Capability, State, and Shadow Invariants

arXiv:2607.20488v1 Announce Type: new Abstract: Multi-agent LLM frameworks typically fix their team topology at boot time. When an individual agent becomes overloaded at runtime, for example by mixing

AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2607.21588v1 Announce Type: new Abstract: Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale b

Benchmarking Large Language Models on Multi-Sensor Physical Hazard Assessment

arXiv:2607.20476v1 Announce Type: new Abstract: We present an empirical benchmark evaluating how five large language models assess multisensor physical hazard data. Testing 60 scenarios across three c

Benchmarking the Personalization Capabilities of Large Language Models

arXiv:2607.20471v1 Announce Type: new Abstract: Personalization, the act of varying a message to induce action from a specific receiver while keeping sender, channel, and time fixed, has a long tradit

Benchmarking Unlearning for Vision Transformers

arXiv:2602.20114v2 Announce Type: replace-cross Abstract: Machine unlearning (MU) refers to the post-training capability to remove (the influence of) training examples that are incorrect, biased, or l

Beyond Liars' Bench: The Impact of Lie Typology, Depth, and Sparsity on Deception Detection in LLMs

arXiv:2607.20479v1 Announce Type: new Abstract: Training probes to detect deceptive outputs from large language models is still an open problem. Recent work has demonstrated that detection probes fail

Break Through the Compression Bottleneck: From Theory to Practice

arXiv:2607.20434v1 Announce Type: cross Abstract: As the parameter size of language models continues to grow, effective model compression is required to reduce their computational and memory overhead.

CAMeR: Keyword-Gated Hybrid Activation for Adaptive Memory Retention in LLM Agents

arXiv:2607.20458v1 Announce Type: cross Abstract: Large language model (LLM) agents operating over extended dialogues accumulate vast amounts of information, yet existing memory systems either retain

CANN Bench: Benchmarking Agent Generated Kernels against Real NPU and Algorithmic Limits

arXiv:2607.20518v1 Announce Type: new Abstract: AI agents are now capable of writing, compiling, and iteratively optimizing low-level operator kernels on different hardware platforms. Existing benchma

Capital Markets LLM Reliability Score (CM-LRS): From Plausible to Bankable

arXiv:2607.21340v1 Announce Type: new Abstract: In capital-markets workflows the question is rarely whether a large language model can produce a fluent draft, but whether the draft is bankable: defens

Cardinality-Decomposed Loss: Matching Training Objectives to Relation Structure in Heterogeneous Recommendation Graphs

arXiv:2607.20737v1 Announce Type: new Abstract: Graph Neural Networks trained on heterogenous bipartite graphs form a common basis in recommendation systems. These graphs often express relations that

Case study: solving P-99 with LPTP and an LLM

arXiv:2607.21196v1 Announce Type: cross Abstract: Ninety-Nine Prolog Problems (P-99) is a famous set of Prolog exercises. We solved the first thirty three just by prompting an LLM (Large Language Mode

Chronofy: A Temporal-Logical Decay Architecture for Information Validity in Time-Aware Retrieval-Augmented Generation

arXiv:2607.20560v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems retrieve and integrate external knowledge to ground large language model (LLM) outputs. However, current RA

Classifier-pruned Bayesian optimization for particle accelerator tuning: Exploring temporally structured manifold of 6D beam phase space

arXiv:2412.01748v2 Announce Type: replace Abstract: Complex dynamical systems, such as particle accelerators, often require intricate and time-consuming tuning procedures to achieve optimal performanc

ConfidenceBench: Evaluating Confidence Calibration in Large Language Models

arXiv:2607.20526v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in settings where fluent but incorrect answers can be costly. In these settings, accuracy alone i

CRAG-MM-Diagnostics: Enabling Stage-Wise Analysis of Knowledge-Intensive VQA

arXiv:2607.21155v1 Announce Type: cross Abstract: Knowledge-Intensive Visual Question Answering (KI-VQA) benchmarks evaluate Vision-Language Models (VLMs) as multimodal knowledge assistants by requiri

CT-Merging: Consensus Directions and Task-Level Scaling for LoRA Adapter Merging

arXiv:2607.20561v1 Announce Type: cross Abstract: LoRA adapters provide an efficient way to specialize a pretrained model for many downstream tasks, but deploying one adapter per task requires adapter

CultureTalk-ID: A Multi-Task Dialogue Benchmark for Cultural Commonsense in Indonesian Local Languages

arXiv:2607.21016v1 Announce Type: new Abstract: Culture is lived through conversation, yet existing Indonesian cultural commonsense benchmarks evaluate LLMs on short and isolated prompts, stripping aw

Cycle-Consistent and Uncertainty-Aware Neural Surrogates for Tokamak Edge Plasmas

arXiv:2607.21407v1 Announce Type: cross Abstract: The boundary and divertor plasma govern how a tokamak exhausts power and particles, setting heat fluxes, target conditions, and the onset of detachmen

DataPrep-Bench: Benchmarking LLMs as Training Data Preparators

arXiv:2607.20465v1 Announce Type: cross Abstract: The quality of training data fundamentally determines the capabilities of large language models (LLMs), yet no unified benchmark exists to measure how

DatedGPT: Preventing Lookahead Bias in Large Language Models with Time-Aware Pretraining

arXiv:2603.11838v2 Announce Type: replace Abstract: Large language models pretrained on internet-scale data risk lookahead bias in forecasting tasks, as they may have already seen the true outcome dur

Deblurring in the Wild: A Real-World Image Deblurring Dataset from Smartphone High-Speed Videos

arXiv:2506.19445v4 Announce Type: cross Abstract: We introduce the largest real-world image deblurring dataset constructed from smartphone slow-motion videos. Using 240 frames captured over one second

Demonstrating GenDB: Instance-Optimized and Customized Query Processing Code Generation via LLM Agents

arXiv:2607.20630v1 Announce Type: cross Abstract: Traditional query processing engines require continuous development and extensions to support new techniques and user requirements, and in some cases,

Detecting Neural Network Failures through Spectral Analysis of Internal Activations

arXiv:2607.20590v1 Announce Type: cross Abstract: Neural network misclassifications exhibit characteristic spectral instability in internal activations that is invisible at the output layer. This phen

DFAH-Bench: Benchmarking Observable Agent Instability in Financial Decision-Making

arXiv:2607.20491v1 Announce Type: new Abstract: Standard evaluation benchmarks measure what a tool-using agent decides, not whether it arrives at that decision through the same process each time. We i

DINO-VPT: Hierarchical Visual Prompt Tuning for Joint Physical-Digital Face Anti-Spoofing

arXiv:2607.20900v1 Announce Type: new Abstract: With the increasing diversity of spoofing attacks, there is a growing demand for unified Face Anti-Spoofing (FAS) models capable of detecting both physi

Do Active SAE Feature Planes Carry More Holonomy? A Preregistered Reversal in Gemma

arXiv:2607.20522v1 Announce Type: new Abstract: This paper tests whether holonomy concentrates on active sparse-autoencoder (SAE) feature planes in Gemma 2 2B, a concrete operationalization of the bro

Do Pathology Vision-Language Models Truly See Pathology?

arXiv:2607.21065v1 Announce Type: new Abstract: Pathology vision-language models (VLMs) have recently progressed rapidly and are commonly evaluated by answer accuracy on pathology VQA benchmarks. Howe

Domyn-Small: A European 10B Reasoning Language Model

arXiv:2607.20448v1 Announce Type: new Abstract: We introduce Domyn-Small, a 10-billion-parameter open-weight reasoning language model released under the MIT license. Domyn-Small is the product of an i

DONDO: Open w2v-BERT Speech-Recognition Base Models for African Languages

arXiv:2607.21540v1 Announce Type: new Abstract: We present DONDO, a family of open, permissively licensed automatic speech recognition (ASR) base models for African languages, built on the w2v-BERT 2.

Drive As You Like: Multi-Head Diffusion with Reinforcement Learning for Personalized Driving

arXiv:2508.16947v2 Announce Type: replace-cross Abstract: Despite significant progress, imitation learning-based autonomous driving planners remain largely restricted to reproducing high-frequency bia

Dropping the Anchor: Statistical Context Summarization for Distributed Systems via Pulsar Attention

arXiv:2607.20457v1 Announce Type: cross Abstract: Inference with large language models (LLMs) on long sequences is computationally expensive due to the quadratic complexity of self-attention. Distribu