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Computation & Language / NLP
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Newest papers, page 237
Exact Quantile Balancing and Load-Error Injection for Mixture-of-Experts
Mixture-of-Experts (MoE) training requires global load balance to prevent expert under-utilization and local balance for efficient expert-parallel execution.A Native-Reference Coordinate Geometry for L2 Pronunciation Deviation Using Self-Supervised Speech Models
Self-supervised speech models encode rich phonetic information, but it remains unclear how to transform this information into interpretable metrics for second-language (L2) pronunciation assessment…Reference-Based Analysis of Coherence and Diversity in Open-Ended Text Generation
Evaluating open-ended text generation involves understanding how different properties of a continuation relate to its perceived quality.Can LLMs Catch a Rigged Backtest? A Clean-Control Calibration Benchmark
Backtest auditing is a calibration problem: high flaw recall is not useful when the model falsely flags matched clean strategies.Scaling Attention Head Analysis via Gradient-Based Attribution in Context-Aware Machine Translation
In this paper, we introduce a gradient-based head attribution strategy where the Token-level Max-Margin loss is backpropagated to the attention maps.Exact Feedback Is Not Control: Evaluating Text-based Closed-Loop Revision in LLMs
Closed-loop revision is increasingly used in large language model (LLM) applications, but failures may reflect incomplete feedback or ineffective responses to correct feedback.PASTABench: Proactive Assessment of Sequential Trajectories for Agent Safety
As Large Language Models (LLMs) evolve into autonomous agents that alter real-world states, ensuring operational safety across multi-step workflows has become a critical challenge.Log-Depth Recurrent Language Modeling
Language modeling using Transformers has become commonplace despite their fixed computational depth and quadratic runtime with respect to input tokens.Beyond Poetry: Can Large Language Models Generate Classical Arabic Maqamat?
Large language models (LLMs) have shown strong performance in creative text generation, yet their ability to produce culturally grounded and stylistically constrained literary forms remains…Complementary Roles of Activation and Parametric Memory in Few-Shot Learning
At test time, large language models (LLMs) can encode historical information in activation memory (i.e., KV caches) and parametric memory (i.e., updated parameters).Predicting Quantization Price for Selecting PTQ Configurations Before Deployment
Weight-space post-training quantization (PTQ) must choose finite formats, granularities, quantizer families, transformations, and bits before the completed quantized model reveals its…Towards Efficient Reasoning: Learning Causal Shortcuts for Diffusion Language Models
Diffusion Language Models (DLMs) have attracted significant attention for their strong reasoning ability.Shutdown Sabotage Propensities in Multi-Agent Systems
The final safeguard against rogue AI behavior is the human ability to shut systems down.Computation Over Geometry: Meaning Identity Is Computed, Not Shipped in the Embeddings
Meaning identity (whether two sentences say the same thing after wording changes) is treated in retrieval and RAG as a geometric fact about independently encoded sentence vectors.Mizar: A 159M-Parameter Audio-Language Model for Audio Understanding
Audio-language models (ALMs) integrate acoustic perception with the knowledge encoded in language models, enabling contextual understanding of auditory events.Digital diglossia: Arabic between X and Facebook
This study highlights the distribution of Standard Arabic (SA; H(igh) variety) and Colloquial Arabic (CA; L(ow) variety) across X and Facebook.Fine-Tuning LLMs for Translation: General Forgetting Mitigation Does Not Preserve MT-Specific Instruction Following
Fine-tuning large language models on parallel data improves translation quality but can cause catastrophic forgetting.Agent-Editing World Model: Rethinking World Modeling for LLM Agents
Recent advances in large language models (LLMs) have enabled agents to tackle long-horizon tasks across diverse environments.Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms
This work addresses continuous depression-severity score prediction from clinical interview transcripts under data scarcity.Order-Invariant Answers, Order-Sensitive Representations in Mathematical Reasoning
Reordering a set of mathematical rules without changing its meaning should preserve the correct answer, but must a model's internal representations stay invariant too?