Large Language Models

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Large Language Models(Llms

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Large Language Model Output

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Acceptance-Test-Driven Evaluation Protocols for Business-Centric LLM Systems
Jun 1, 2026Eric LiangLarge Language Model Evaluation Evaluation Protocols
Auditing Asset-Specific Preferences in Financial Large Language Models: Evidence from Bitcoin Representations and Portfolio Allocation
Jun 1, 2026Wenbin WuLarge Language Model Decision-Making Portfolio Optimization
Algorithmic algorithm development with LLMs: A Case Study on LLM-Usage for Contraction Order Optimization in Tensor Networks
Jun 1, 2026Fabian Hoppe, Melven Röhrig-Zöllner, Philipp KnechtgesEvolutionary Search Alphaevolve
Mechanistic Diagnostics of Spatial Lexical Bias in Multimodal Large Language Model Spatial Reasoning
Jun 1, 2026Chuang Ma, Qianying Liu, Tomoyuki Obuchi +6Multi-Modal Large Language Models Spatial Reasoning
Unveiling the Limits of Large Language Models in Inferring Pragmatic Meaning from Non-Verbal Responses
Jun 1, 2026Sugyeong Eo, Heuiseok LimNonverbal Cues Large Language Model Performance
EstRTL: Functional Estimation Guided RTL Code Generation
Jun 1, 2026Qi Xiong, Renzhi Chen, Bowei Wang +3Flexible Register Transfer Level Design Automation Register Transfer Level
LLM Consortium for Software Design Refinement: A Controlled Experiment on Multi-Agent Collaboration Topologies
May 31, 2026Nagarjuna Kanamarlapudi, Praveen KMulti-Agent Large Language Model Collaboration
Beyond Access: Guided LLM Scaffolding for Independent Learning in Undergraduate Statistics
May 31, 2026Mohammad Amanlou, Yasaman Amou-Jafari, Mehrad Livian +3Large Language Probability
A Communication-Centric 6G-LLM Architecture for Scalable Tactical Autonomous Defense Vehicle Networks
May 31, 2026Kiran Khurshid, Shumaila Javaid, Nasir SaeedEdge Computing Llm-Driven
A New Framework for Cybersecurity Refusals in AI Agents
May 31, 2026Eliot Krzysztof Jones, Mateusz Dziemian, Matt Fredrikson +1Cybersecurity Artificial Intelligence Safety
When Data Is Scarce: Scaling Sparse Language Models with Repeated Training
May 31, 2026Boqian Wu, Qiao Xiao, Patrik Okanovic +6Large Models Data Scarcity
Relational Intervention During Functional Collapse in Large Language Models: A Lexical-Statistical Ablation and a Structure x Register Factorial
May 31, 2026Franco Santana, Horacio VicoDissociation Ablation
Mitigating Hallucinations in Large Language Models Via Decoder Layer Skipping
May 30, 2026Hanze Li, Jinhao You, Yichen Guo +3Large Language Model Hallucination Hallucination Mitigation
LLM-Driven Co-Evolutionary Automated Heuristic Design for Bi-Component Coupled Combinatorial Optimization
May 30, 2026Mingen Kuang, Xudong Deng, Xi Lin +3Co-Evolution Combinatorial Optimization
ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression
May 30, 2026Wenya Yu, Chao Zhang, Li Wang +2Large Language Model Quantization Large Language Model Compression
From "Weak" Signals to Strong Models: Preference Delta Aggregation with LoRA Merging
May 29, 2026Qi Sun, Siyue Zhang, Yulin Chen +3Large Language Low-Rank Adaptation
Capability Self-Assessment: Teaching LLMs to Know Their Limits
May 29, 2026Haoyan Yang, Reza Shirkavand, Yukai Jin +3Large Language Model Performance Self-Assessments
Effects of Varying LLM Access on Essay Writing Behavior
May 29, 2026Julia Christenson, Karin de Langis, Shirley Anugrah Hayati +1Writing Large Language Model Performance
Language Models Can Resolve Reference Compositionally, But It's Not Their Native Strength: The Case of the Personal Relation Task
May 29, 2026Bart Evelo, Meaghan Fowlie, Denis PapernoLarge Language Model Performance Personalization
Translation Analytics for Freelancers II: Benchmarking Local LLMs for Confidential Translation Workflows
May 29, 2026Yuri Balashov, Rex VanHorn, Mingxi Xu +1Machine Translation Models Neural Machine Translation Models
The Sword, Shield, and Achilles' Heel: Characterizing the Linguistic Inductive Bias of Large Language Models for Spatial Reasoning in Navigation Planning
May 29, 2026Xudong Zhang, Jian Yang, Shengkai Wang +5Large Language Model Planning Spatial Reasoning
Target-Side Paraphrase Augmentation for Sign Language Translation with Large Language Models
May 29, 2026Pedro Dal Bianco, Jean Paul Nunes Reinhold, Oscar Stanchi +3Sign Language Recognition Paraphrasing
On the Robustness of Multilingual Text Embedding Rankings Across Learning Tasks, Languages, and Benchmark Datasets
May 29, 2026Ana Gjorgjevikj, Barbara Koroušić Seljak, Tome EftimovDomain-Invariant Text Embeddings Multilingual
How Much Do LLMs Know About Chinese Zero Pronouns?
May 29, 2026Yifei Li, Guanyi Chen, Tingting HeLarge Language Model Performance Pronoun
Cognitive Fatigue in Autoregressive Transformers: Formalization and Measurement
May 29, 2026Riju Marwah, Ritvik Garimella, Vishal Pallagani +3Autoregressive Language Models Large Language Model Performance
Office Comprehension Benchmark
May 29, 2026Firoz Shaik, Mateus Picanço Lima Gomes, Tanvir Aumi +17First Comprehensive Benchmark Large Language
The Long-Term Effects of Data Selection in LLM Fine-Tuning
May 28, 2026Yuxin Yang, Aoxiong Zeng, Xiangquan YangLarge Language Model Fine-Tuning Large Language
Can LLM Teams Play What? Where? When?
May 28, 2026Anastasia Kotelnikova, Viktor Byzov, Maria Dolzhenkova +1Multi-Agent Large Language Model Large Language Model Performance
LLMSurgeon: Diagnosing Data Mixture of Large Language Models
May 28, 2026Yaxin Luo, Jiacheng Cui, Xiaohan Zhao +5Large Language Mixtures
SchGen: PCB Schematic Generation with Semantic-Grounded Code Representations
May 28, 2026Qinpei Luo, Ruichun Ma, Xinyu Zhang +1Computer-Aided Design Consumer Hardware
Unlocking the Working Memory of Large Language Models for Latent Reasoning
May 28, 2026Lukas Aichberger, Sepp HochreiterEfficient Latent Reasoning Large Language
MIRA: Mid-training Rubric Anchoring for Source-Aware Data Selection
May 28, 2026Haowen Wang, Yaxin Du, Jian Yang +9Large Language Rubrics
Do Proactive Agents Really Need an LLM to Decide When to Wake and What to Anchor?
May 28, 2026Xiaoze Liu, Ruowang Zhang, Amir H. Abdi +5Proactive Large Language Models(Llms
Protocol for evaluating ChatGPT in biomedical association generation and verification using a RAG-enabled, cross-model majority voting workflow
May 28, 2026Ahmed Abdeen Hamed, Luis M. RochaMedical Ontology Clinical Reasoning
How Reliable Are AI Attackers Against a Fixed Vulnerable Target? A 400-Run Empirical Study of LLM Penetration Testing Consistency
May 28, 2026Galip Tolga ErdemLanguage Model Evasion Attacks Penetration Testing
Token Inflation: How Dishonest Providers Can Overcharge for Large Language Model Usage
May 28, 2026Shahinul Hoque, Jinghuai Zhang, Jinyuan Sun +1Algorithm Auditing Large Language
Latent Performance Profiling of Large Language Models
May 28, 2026Tanmoy Chakraborty, Ayan Sengupta, Suparna Bhattacharya +7Large Language Profiling
Internal Representation, Not Clinical Knowledge: Where Apparent LLM Triage Failures Originate
May 28, 2026David Fraile Navarro, Berardino Como, Jialei Sheng +2Large Language Model Performance Multiple-Choice Questions
DySem: Uncovering Dynamic Semantic Components of Large Language Models for Calculating Semantic Textual Similarity
May 28, 2026Kaijie Zheng, Weiqin Wang, Yile Wang +1Geo-Contextual Alignment Domain-Invariant Text Embeddings
Minimal Prompt Perturbations Lead to Code Vulnerabilities: Prompt Fragility and Hidden-State Signals in Coding LLMs
May 28, 2026Alexander Sternfeld, Andrei Kucharavy, Ljiljana DolamicVulnerable Code Vulnerability Detection & Repair
BitTP: The Lightweight Trajectory Prediction Model with BitLLM for Edge-Devices
May 28, 2026Mincheol Kang, Hyunjin Lim, Bomin Kang +1Large Language Model Quantization Trajectory Prediction
DynaGraph: Lightweight Multi-Model Interaction Framework via Dynamic Topological Reconfiguration
May 28, 2026Yanxing Guo, Zihao Zheng, Fangzhou Wu +4Reasoning Graphs Large Language
Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet
May 28, 2026Adly Templeton, Tom Conerly, Jonathan Marcus +23Sparse Autoencoder Features Model Interpretability
LLM-ALSO: LLM-Driven Adaptive Learning-Signal Optimization for Multi-Agent Reinforcement Learning
May 28, 2026Xiaoguang Wu, Zhi Zheng, Hui XiongMulti-Agent Reinforcement Learning Unseen-Task Adaptation
Accommodation Goes Both Ways: Studying Linguistic Convergence Between Humans and Language Models
May 28, 2026Terra BlevinsLinguistics Multi-Turn Large Language Model Conversations
Compute Allocation in Evolutionary Search: From Depth-Breadth to Multi-Armed Bandits
May 28, 2026Sixue Xing, Haoyu He, Kerui Wu +4Evolutionary Search Multi-Armed Bandits
Apertus LLM Family Expansion via Distillation and Quantization
May 27, 2026Andrei Panferov, Davit Melikidze, Martin Jaggi +1Large Language Model Quantization Large Language
Can Large Language Models Handle Discourse Particles? A Case Study of Colloquial Malay
May 27, 2026Mariah Al Giptiah Binte Yusoff, Jakin Tan, Bocheng Chen +2Large Language Model Performance Linguistics
MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems
May 27, 2026Xinle Deng, Ruobin Zhong, Hujin Peng +15Large Language Model Memory Large Language Model Performance
The Ethics of LLM Sandbox and Persona Dynamics
May 27, 2026Tim Gebbie, Stewart GebbieEthics Large Language Model Safety
Efficient and Scalable Provenance Tracking for LLM-Generated Code Snippets
May 27, 2026Andrea Gurioli, Davide D'Ascenzo, Federico Pennino +2Code Quality Code Generation
Revisiting Anthropomorphic Reflection Markers in Large Language Model Reasoning
May 27, 2026Yahan Yu, Noa Nakanishi, Fei ChengLarge Language Model Reasoning Large Language Model Performance
Do LLMs Build World Models From Text? A Multilingual Diagnostic of Spatial Reasoning
May 27, 2026Zhikai Pan, Chih-Ting Liao, Chunrui Liu +5Large Language Model Performance Spatial Reasoning
Explaining is Harder Than Predicting Alone: Evaluating Concept-based Explanations of MLLMs as ICL Visual Classifiers
May 27, 2026Carmen Quiles-Ramírez, Leticia L. Rodríguez, Nicolás Martorell +1Explainability Multi-Modal Large Language Models
BenGER: Benchmarking LLM Systems on Subsumption-Based Legal Reasoning in German Law
May 27, 2026Sebastian Nagl, Ann-Kristin Mayrhofer, Martin Heidebach +6Legal Domain German
SMILE-Next: Teaching Large Language Models to Detect, Classify, and Reason about Laughter
May 27, 2026Lee Jung-Mok, Kim Sung-Bin, Joohyun Chang +2Humor Multi-Modal Large Language Models
Knowing When to Ask: Segment-Level Credit Assignment for LLM Tool Use
May 27, 2026Abhijit Kumar, Zoey Wu, Mohit SuleyLarge Language Model Calls Tool
Poison with Style: A Practical Poisoning Attack on Code Large Language Models
May 26, 2026Khang Tran, Yazan Boshmaf, Issa Khalil +3Language Model Evasion Attacks Data Poisoning
Hallucination Behavior in Multimodal LLMs Across Agricultural Image Interpretation and Generation Tasks
May 26, 2026Partho Ghose, Al Bashir, Prem Raj +1Large Language Model Hallucination Hallucination Rate
Why LLMs Fail at Causal Discovery and How Interventional Agents Escape
May 26, 2026Amartya Roy, Sonali ParbhooLarge Language Model Performance Finetuning

Jun 1, 2026 · cs.SEJ/K move · Enter open · S save

Acceptance-Test-Driven Evaluation Protocols for Business-Centric LLM Systems

Eric Liang

Oracle

Large language model (LLM) applications are increasingly expected to satisfy deterministic institutional requirements while relying on probabilistic generative components. This mismatch makes ordinary post-hoc benchmarking insufficient for systems that must be safe, reliable, auditable, and economically useful. This paper contributes an evaluation-protocol extension for operational LLM systems grounded in acceptance-test-driven development, safety engineering, and business-centric validation. The extension translates stakeholder goals into executable behavioral contracts, release gates, monitoring signals, and evidence artifacts before prompt, model, retrieval, or agent changes are accepted. It adapts the red-green-refactor discipline of test-driven development to a red-train-green lifecycle: first define failing acceptance tests for desired behavior, then improve the LLM system through prompt changes, retrieval design, fine-tuning, guardrails, or data augmentation, and finally release only when multidimensional gates are satisfied. The contribution is a governance-oriented metric stack, reference architecture, and empirical protocol for comparing acceptance-test-driven LLM development against prompt-first and benchmark-after workflows.

Large Language Model Evaluation Evaluation Protocols Large Language Kernel Contracts Governance

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