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Computation & Language / NLP
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Newest papers, page 82
LoWAgent: A Low-Resource Multilingual Benchmark for Web Agents
Web agents are typically evaluated on English-language interfaces, leaving their ability to operate across the world's multilingual websites largely unexplored.Profile-DP: Differential Privacy for User-Controlled Profile Release in Personalized LLM Inference
Personalized large language models (LLMs) increasingly rely on profile-conditioned inference, pairing public requests with rich, user-specific facts.Which Agent's Skill Should Change? Group-Relative Credit Assignment for Evolving Multi-Agent Teams
Cooperative language-model agents can improve without weight updates by revising reusable skills, but only if a shared team reward is traced to the responsible agent and skill.MMedAgent-Plus: Scaling Multimodal Medical Agents across Modalities, Tasks and Workflows
Medical workflows often require multiple interdependent analyses, but existing specialist and generalist AI models are not designed to coordinate them.CEFR-oriented Russian Text Simplification Using Reinforcement Learning
We present a study on controlled automatic simplification of Russian texts using preference-based optimization algorithms with a focus on adapting texts to the A1, A2 and B1 proficiency levels.Predicting Linear Relational Decodability Without the Relation
Linear relational embeddings (LREs) approximate a language model's subject-to-object mapping with an affine function.Diagnostic Analysis for Large Language Model Reasoning
Reasoning structures (e.g., chains and graphs) are increasingly used for probabilistic inference, factuality verification, and uncertainty estimation, but their structural reliability is rarely…Target-Aware Curation of Hallucination Stress Tests for Large Language Models
Hallucination stress tests can yield similar average scores across language models even when different prompts elicit hallucinations in each model.TxnQA: Benchmarking Analytical Reasoning and Evidence Grounding over Transaction Event Sequences
Analyzing merchant transaction histories requires dynamic temporal filtering, entity resolution, and aggregation over irregular event streams--operations poorly captured by static tabular or…Auditing Safety Preference Supervision with Recorded Derivations
Preference labels align model training, but the judgments behind them are difficult to inspect or verify.African Languages AI Safety Readiness Report
With the widespread adoption of large language models (LLMs) across languages and domains, AI safety has emerged as a critical global concern.FLINT: Fixed-budget Late Interaction
Multi-vector retrieval models such as ColBERT often outperform single-vector models of comparable scale by matching queries and documents at the token level.When Does Hate Transfer? A Large-Scale Study of Cross-Lingual Hate Speech Detection
Effective detection of hate content is essential for maintaining healthy online communities, yet performance can vary substantially across languages.TEX: Test-Time Scaling Testing Agents via Execution-based Cross-Validation
Test-case generation is critical but remains challenging for language models.RealControlBench: A Benchmark for Interpretability-Informed Fine-Grained Control of LLMs and Agents
Existing steering benchmarks are built around simplified, isolated generation tasks and evaluate a single behavioral attribute under controlled settings that do not reflect the diversity and…Evaluating Context Compaction on the Questions That Come Later
Language-model agents compact their context for the question at hand, but the compacted context must also serve questions that come later.Global Security Blind Spots: Translation as a Safety Bypass in Low-Resource Languages
Large language models are deployed globally, yet safety alignment and evaluation remain concentrated in English: harmful requests refused in English can elicit unsafe completions when translated…On the LLM Verification for Argument Graph Generation
Multi-agent LLM systems can formalize natural-language argumentation end-to-end, turning plain text into structured graphs by classifying components, connecting them with relations, and enriching…Explore More, Validate Less: Efficient Reflective Prompt Optimization
Reflective prompt optimization improves instructions using task feedback, but coupling candidate generation with full-validation-based selection can make search costly and sequential.SHAM-Bench: A Span-level Hallucination Benchmark Across Multiple Tasks
Span-level hallucination detection pinpoints unsupported content in LLM outputs, enabling actionable feedback and targeted mitigation.