Search: “llm”

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-

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

DGX agent

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

model-releasesarxiv-cs-cl

1 Sept 2026

CM2: Multimodal Cultural Reasoning via an Integrated Multi-Agent Framework

arXiv:2608.30498v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown remarkable success in STEM domains, where progress is often driven by vertical, step-by-step deducti

Conducting Stylistic Analysis of Paintings through an Art-History Agent

arXiv:2608.29644v1 Announce Type: cross Abstract: Attributing an artwork to an artist has traditionally relied on detailed visual observations and descriptions, known as stylistic analysis in art hist

Context Staircase: Signature-Aligned Dynamics of Token Embeddings under Small Initialization

arXiv:2608.30315v1 Announce Type: cross Abstract: Token embeddings are the basic representational units that connect discrete tokens with continuous computation in language models. Although modern lan

CrossAudit: A Git-Native, Cross-Vendor Audit Loop for Agentic Science

arXiv:2608.28631v1 Announce Type: new Abstract: An AI scientist should not grade its own homework. Yet in the systems we examined, the agent that reviews the work usually comes from the same model fam

Curvature Cryptanalysis of Smooth Transformer Feed-Forward Networks

arXiv:2608.28843v1 Announce Type: cross Abstract: We show that smooth two-layer feed-forward networks (FFNs) expose an additional structural model extraction channel under a chosen-input raw-output or

Applications

DataFoundry: Evolving Data Preparators via Recursive Self-Improvement

arXiv:2608.29966v1 Announce Type: new Abstract: Domain adaptation of large language models increasingly depends on constructing high-quality training data, yet existing data-preparation pipelines typi

applicationsarxiv-cs-cl

Delegating Before Learning: Where Generative AI Sits in Students' Professional Communication

arXiv:2608.28837v1 Announce Type: cross Abstract: We conducted an interview study with twelve students on their use of generative AI in academic communication. Students delegated professional messages

Dense Clinical Contrasts Enhance Medical Knowledge Updating in Large Language Models

arXiv:2608.30405v1 Announce Type: new Abstract: Medical knowledge changes continually, making large language models vulnerable to relying on outdated yet clinically plausible information. We study whe

Detecting Hidden Chain-of-Thought in Large Language Models with Linguistic, Behavioral, and Mechanistic Indicators

arXiv:2608.29956v1 Announce Type: new Abstract: Large language models often answer complex reasoning questions without revealing intermediate steps, raising whether they reason latently or complete pa

Domain Mixture Design via Log-Likelihood Differences for Aligning Language Models with a Target Model

arXiv:2603.16622v2 Announce Type: replace Abstract: Instead of directly distilling a language model, this study addresses the problem of aligning a base model with a target model in distribution by de

ECGQuest: Benchmarking and Fine-Tuning Language Models for Electrocardiography

arXiv:2608.30893v1 Announce Type: new Abstract: Electrocardiogram (ECG) interpretation requires knowledge of cardiology, electrophysiology, clinical diagnosis, ECG waveforms, signal acquisition, and i

Error Detection for PET/CT Radiology Reports: Domain-Specific vs Large Language Models

arXiv:2608.30021v1 Announce Type: cross Abstract: Errors in radiology reports can adversely affect patient treatment, yet automated report quality assurance remains challenging because errors are ofte

Error-Driven Scene Editing for 3D Grounding in Large Language Models

arXiv:2511.14086v2 Announce Type: replace-cross Abstract: Despite recent progress in 3D-LLMs, they remain limited in accurately grounding language to visual and spatial elements in 3D environments. Th

FAA Framework: A Large Language Model-Based Approach for Credit Card Fraud Investigations

arXiv:2506.11635v2 Announce Type: replace-cross Abstract: Credit card fraud mitigation plays a significant role in modern society. While fraud detection systems are essential, they often struggle to k

FLM: Frequency-Aware Language Models for Generative Image Compression

arXiv:2608.28687v1 Announce Type: new Abstract: Generative models have significantly improved the performance ceiling of image lossy compression at low bitrates by exploiting learned priors. However,

researcharxiv-cs-cv

Applications

Forget or Fine-tune? A Comparative Study of Machine Unlearning Strategies for Noisy Label Correction

arXiv:2608.30046v1 Announce Type: cross Abstract: Noisy labels remain a critical challenge for training deep neural networks, since memorizing incorrect labels degrades generalization. Once noisy samp

applicationsarxiv-cs-ai

Forward-Deployed Full-Stack Engineering for Autonomous Cloud MLOps

arXiv:2608.29615v1 Announce Type: cross Abstract: Across industries, machine-learning systems support applications ranging from prediction and anomaly detection to forecasting, optimization, and sched

From AGI to ASI

arXiv:2606.12683v2 Announce Type: replace Abstract: Over the last decade, building human-level artificial general intelligence has moved from far-fetched speculation to being a concrete next-decade ta

Local Ai

From GenAI Virtual Patient Dialogue Logs to Teacher-Interpretable Process Evidence: A Learning Analytics Study in Higher Education

arXiv:2608.28619v1 Announce Type: cross Abstract: Medical history taking is a dialogue-based clinical reasoning task in which learners must gather, organise, and integrate patient information while th

local-aiarxiv-cs-ai

GUI-PRA: Process Reward Agent for GUI Tasks

arXiv:2509.23263v3 Announce Type: replace Abstract: Long-horizon GUI automation remains challenging due to error accumulation over extended interaction sequences. Process Reward Models (PRMs) provide

HalluPrism: When Multimodal Uncertainty Should Diagnose, Not Decide

arXiv:2608.29193v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) can assign similar confidence to answers that fail for different reasons. We propose HalluPrism, a behavioral d

researcharxiv-cs-lg

HeTGB: A Comprehensive Benchmark for Heterophilic Text-Attributed Graphs

arXiv:2503.04822v2 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) have demonstrated success in modeling relational data primarily under the assumption of homophily. However, many

Hi-Q: Hierarchical Evidence-guided Query Refinement for Multi-Hop Question Answering

arXiv:2608.30468v1 Announce Type: new Abstract: A central bottleneck in multi-hop Question Answering (QA) is that the granularity at which a question is expressed often differs from the granularity at

researcharxiv-cs-cl

HintEval: An Open-Source Python Toolkit for Hint Generation and Hint Evaluation

arXiv:2502.00857v2 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly provide direct answers to user questions, raising concerns about reduced engagement in critical thinking a

researcharxiv-cs-cl

How Language Models Choose Sides: Internal Representations of Instruction Hierarchy

arXiv:2608.28648v1 Announce Type: new Abstract: We study how instruction-tuned LLMs arbitrate direct conflicts between system and user instructions. We introduce a benchmark of 41 paired constraints w

Hardware

How to Size GPUs for AI Inference and TCO Without Overspending

Inference workloads fall into four use‑case buckets (Chatbots/Copilots, Agents, Content Generation, Translation), each with distinct token patterns that dictate the required GPU memory and compute. Si

hardwarenvidia-developer

How we eliminated $1 million a year of wasted AI agent spend in one hour

The post explains how a quick, one‑hour audit of AI agent usage revealed $1 million per year in avoidable spend. By reviewing deployment patterns and trimming unnecessary calls, the team reallocated r

agentsdatabricks

HumanStudy-Bench: Towards AI Agent Design for Participant Simulation

arXiv:2602.00685v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as simulated participants in social science experiments, but their behavior is often unstable and

Improving Information Extraction with Learned Queries

arXiv:2608.31058v1 Announce Type: new Abstract: When information extraction fails, a natural instinct is to improve the model doing it: for example, by scaling it up or refining its reasoning. In this

Intelligent Identification and Repair of Design Defects in BIM via Domain-Specific Large Language Models

arXiv:2608.28629v1 Announce Type: cross Abstract: Existing methods lack a generalized approach to efficiently identify and resolve the diversity of design defects in BIM. Therefore, this study propose

Interpretable Predictability-Based AI Text Detection: A Replication Study

arXiv:2603.15034v2 Announce Type: replace-cross Abstract: This paper replicates and extends the system used in the AuTexTification shared task for authorship attribution of machine-generated texts. Ex

Interpreting and Steering for Safe and Correct Code Generation

arXiv:2608.30025v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate source code containing vulnerabilities, yet little work studies the internal mechanisms that distinguis

Investigating Social Bias Changes in Quantized Language Models

arXiv:2602.06181v2 Announce Type: replace Abstract: Post-training quantization reduces the memory needed to run large language models but alters their social biases in ways that aggregate metrics fail

Kinship Data Benchmark for Multi-hop Reasoning

arXiv:2601.07794v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly evaluated on their ability to perform multi-hop reasoning, i.e., to combine multiple pieces of i

Label Semantic Expansion via Label Guided Neural Topic Modeling

arXiv:2608.30216v1 Announce Type: cross Abstract: Topic models are widely used for content analysis, where users often analyze corpora around predefined labels rather than unordered latent topics. Exi

Large Language Models Systematically Favor Popular Options: Evidence and Mitigation Across MCQs

arXiv:2608.29257v1 Announce Type: new Abstract: Multiple-choice questions (MCQs) are a standard format for evaluating large language models (LLMs), yet the popularity of answer options can confound ev

Last Step Matters: Early Uncertainty Cannot Predict Failure in Long-Horizon Agents

arXiv:2608.29685v1 Announce Type: new Abstract: Early failure prediction is important for long-horizon agents, as it enables timely intervention and can reduce inference and tool-use costs. Uncertaint

agentsarxiv-cs-lg

LCoT-GV: Graph Attention Networks for Verifying Long Reasoning Chains in Large Language Models

arXiv:2608.30679v1 Announce Type: cross Abstract: Large Reasoning Models produce Long Chains-of-Thought (LCoTs) which involve breaking down the problem into smaller reasoning steps before reaching the

Learning-Assisted Congestion-Aware Route Scheduling for Semiconductor Fab Material Control Systems

arXiv:2608.30520v1 Announce Type: new Abstract: Automated material handling systems in semiconductor fabs are operated by a material control system (MCS) that must schedule a relay route for every tra

Learning diverse attacks on large language models for robust red-teaming and safety tuning

arXiv:2405.18540v3 Announce Type: replace Abstract: Red-teaming, or identifying prompts that elicit harmful responses, is a critical step in ensuring the safe and responsible deployment of large langu

LexRubric: A Rubric-Guided Diagnostic Benchmark for Open-Ended Legal Tasks

arXiv:2606.09389v2 Announce Type: replace Abstract: As large language models (LLMs) are increasingly applied to real-world legal tasks, evaluating the reliability of their open-ended legal responses h

Logos: An Agent Harness on a Cross-Process Bus

arXiv:2608.28553v2 Announce Type: replace Abstract: Modern agent systems assemble capabilities at runtime, and this dynamic composition has recently received a complete formal treat ment in the spatio

LongGuard: Mechanistic Analysis and Training-Free Mitigation of Long-Context Failure in Safety Guardrails

arXiv:2608.27580v2 Announce Type: replace Abstract: Safety guardrails serve as the last line of defense against harmful inputs and outputs of large language models (LLMs), yet they are trained and eva

Lucida: Parse, Generate, and Place for Composable Real-to-Sim Scene Modeling

arXiv:2608.30821v1 Announce Type: cross Abstract: Composable scene modeling aims to recover a real indoor scene as complete, editable object assets arranged as observed, giving robot simulation and em

MagicSim: A Unified Infrastructure for Executable Embodied Interaction

arXiv:2606.17511v2 Announce Type: replace-cross Abstract: Robot learning and embodied agents now require simulation to serve as a shared execution substrate linking control, skills, and planning, not

Manaca-1B: An Open, Reproducible Brazilian-Portuguese Language Model and a Tokenizer-Aware, Paired Evaluation

arXiv:2608.30114v1 Announce Type: new Abstract: Brazilian Portuguese remains under-served by open language models, and the few that exist are difficult to reproduce and are often compared without meas