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Computation & Language / NLP
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Tug of Watts: A study on the Energy - Accuracy Trade-off of Large Language Models on Medical Question Answering Tasks
Large Language Models (LLMs) are increasingly used in medical question answering (QA) systems.Maswao: An automatically collected, prepared, and benchmarked dataset for the South African Sign language
Recent advancements in sign language processing can be attributed to developments in both large-scale dataset collection and algorithmic complexity in areas such as pose estimation techniques…User Attributes and Political Ideology Shape LLM Receptiveness in Online Political Debates
Online political discussions increasingly involve AI-mediated participation, as users invoke LLMs to assess contested claims, arbitrate disputes, and respond to opposing viewpoints.A State Change Is Local, Its Consequences Are Not: Dependency-Aware State Revision for Long-Term Agent Memory
Long-lived agents rely on persistent memory of users, tasks and decisions, and this memory must stay consistent with a world that keeps changing.PlagiaCorpus: A Bilingual, Adversarial, and Cross-Lingual Dataset for Forensic Plagiarism Detection
PlagiaCorpus is a bilingual Arabic-English dataset for benchmarking plagiarism and text-reuse detection, including reuse produced by large language models (LLMs) and reuse across languages.Action Verification through Conjecture and Refutation for Language Model Agents
Language model agents increasingly act on users' behalf by manipulating external environments through tools, often from high-level instructions that leave critical task- and environment-specific…Specification-Aware Predictive Uncertainty Decomposition
Classical decompositions of predictive uncertainty, such as the information-theoretic one, are defined for a fixed representation $x$ of the input object.Distilling Literary Sentiment from LLM Annotations into an Ordinal BERT Model
The scarcity of human-annotated literary corpora limits the development of domain-specific sentiment analysis models.Finding Errors Is Not Enough: Selective Model Escalation for Entity-Targeted Sentiment Analysis
Improving a sentiment classifier with limited resources involves more than simply deciding how much data to collect or which model to train.VERS: Steering Reasoning Models by Editing Their Activation Explanations
Reasoning language models write a chain of thought before they answer, and many checks in it do not change the final answer.Unlocking Criminal Court Decisions: Flexible Information Extraction for Empirical Legal Research
Criminal verdicts contain descriptions of criminal behavior that can support quantitative legal research, but structuring them requires attributes and extraction rules that cannot always be fully…SAGE (Subjectivity-Aware Generation Estimator): A Linguistic Framework for AI-Generated Review Detection *
We propose a simple, linguistically motivated approach to detecting AI-generated peer reviews based on the inherently human trait of subjectivity.Avatar Intelligence: Amplifying Human Agency Through Persistent Personal Agents
Personal AI agents are increasingly capable of handling long-horizon tasks across applications, yet users often need to invest substantial effort in specifying goals, resolving ambiguity, and…An Experimental Study of Hybrid Retrieval, NLI and Open-source LLMs for Scientific Claim Verification
Claim verification is the task of deciding whether a source text supports a claim, contradicts it, or lacks sufficient evidence.DR Pixel: Page-Native Deep Research with Vision-Language Models
Complex documents such as scientific papers contain rich information in tables, figures, and equations; however, existing deep research (DR) agents typically reduce papers to OCR-extracted text.Preprocessing Choices in Fine-Tuning Data Matter: Utility and Demographic Sensitivity in LLM-Based Recommendation
Large language models (LLMs) have introduced a generative approach to recommendation, producing item lists from textual representations of user histories and item information.Meet Students Where They Are: Student-Prefix Teacher Adaptation for On-Policy Distillation
On-policy distillation (OPD) mitigates the student's exposure bias by optimizing on student-generated trajectories.DepthGraft: Structural Regularization through Hierarchical Cross-Layer KV Reconstruction
Scaling depth is a key route to stronger large language models, but Pre-LN architectures often suffer from depth-wise information dilution, limiting the effective use of deep layers.ViAdminShift: A Vietnamese Benchmark for Event-Level Knowledge Updates Built from the 2025 Administrative Reform
On July 1, 2025, Vietnam reduced its 63 provinces to 34, abolished its 696 districts, and replaced its 10,035 commune-level units (wards) with 3,321.CoworkOS:Scaling Agent Coworkers for Real-world Automation
Rapid advances in cowork agents are shifting human-AI collaboration toward real-world automation, delivering software, designs, and other artifacts.