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Newest papers, page 67
Every Part Has Its Role: Part-of-Speech Effects in LLM Post-Training
Large language models are typically trained with next-token prediction (NTP), which rewards predicting specific tokens rather than explicitly accounting for the semantic similarities between…Investigating the Impact of Learner Errors on Social Bias in Large Language Models
Existing social bias benchmarks evaluate large language models mostly on fluent, well-formed English, reflecting native speaker usage and leaving non-native writers unrepresented.Benchmarking Large Language Models for Detecting Satirical Code-Mixed Sentences
Code-switching is a natural linguistic phenomenon, yet its impact on high-level reasoning tasks remains largely unexplored in under-resourced languages like Romanian.Unintended Side Effects of Value Training in LLMs
As LLMs are increasingly deployed in value-sensitive contexts, aligning them with human values has emerged as a post-training objective in NLP, aimed at instilling additional values and guiding…Task-Preserving Multilingual Instruction Tuning for Open-Ended QA in WMT 2026 MIST
This paper describes our submission to the WMT 2026 Multilingual Instruction Shared Task.Your Benchmark Is an Empirical Measure Over Difficulty
A benchmark is not merely a collection of test questions; it naturally induces an empirical measure over difficulty.Graph Topology Meets Energy-Driven Pathfinding: Preserving Contextual Consistency in Retrieval-Augmented Generation
Retrieval-augmented generation (RAG) frequently integrates knowledge graphs (KGs) for complex multi-hop question answering.ToM2Vec: Continuous Theory-of-Mind Tokens for Multi-Agent Coordination
Forming an accurate theory-of-mind (ToM) is key to successful multi-agent collaboration and requires reasoning under uncertainty to capture multiple possible partner states.Towards English - Mizo Legal Machine Translation: Corpus Creation, Analysis, and Benchmarks
Indian court proceedings are held in English, so speakers of languages with limited translation technology have limited access to them.Commit or Abstain? System One Decision Models, LLMs, and Missing Legal Authority
Given the enormous number of claims to be checked, verifiable legal AI requires scalable, cost-effective models that answer the practical needs of law.CulturalRiddles: A Multicultural Benchmark of Riddles
As LLMs expand their language coverage, evaluating how well they understand and represent diverse cultures becomes increasingly important.Remembering Through Change: Provenance-Preserving Hypergraph Memory for Multimodal Agents
Long-term memory for multimodal agents remains challenging, as it must preserve fine-grained visual evidence while tracking entity evolution across sessions.HiddenLens: A Multi-Layer LLM Framework for Detecting and Resolving Hidden Assumptions in Software Requirements
Natural-language software requirements often omit assumptions about performance, operating conditions, user behaviour, and domain constraints, affecting architecture, testing, and deployment.Building Auditable AI Text Detectors with Sparse Autoencoders
AI-generated text detectors are increasingly deployed in consequential settings---peer review, education, admissions, journalism, and content moderation---where their outputs directly affect…Agent Behavior Maps: Locating Agents by What They Would Do, Without Running Them
LLM agents with similar success rates can follow different action sequences.What the Author Wrote, What the Agent Reads: Silent Cue Loss in Enterprise Document Ingestion
Enterprise agents act on documents.Looped Uniform Diffusion Language Models
Uniform diffusion language models (UDLMs) generate text by iteratively denoising sequences of ordinary vocabulary tokens, any of which may be corrupted and subsequently revised.GoiBERT: Compact Vietnamese Language Models via Two-Stage Knowledge Distillation
Vietnamese pre-trained encoders have improved rapidly, but the strongest ones are large, multilingual-vocabulary models or depend on external word segmentation, which makes them costly to deploy.VX-One: Typed, Calibrated Decision Heads for Real-Time Perimeter Triage
Perimeter triage faces a latency/semantics trade-off: signature engines are fast and format-safe but blind to unseen attacks, while generative models are semantic but slow and unparseable.Did the Problem Actually Get Harder? Testing LLMs on Paired P and NP-Complete Problems Hardened by Adversarial Multi-Agent Rewriting
Many NP-complete (NPC) problems have a polynomial-time (P) twin that differs in a single structural detail, such as 3- versus 2-colouring a graph.