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Computation & Language / NLP
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Newest papers, page 85
Reranking Answers of Large Language Models with Knowledge Graphs
Answering natural language questions over knowledge graph data is challenging due to the vast number of facts, which can be difficult to process and navigate.Acharya 2.0: An AI Tutor for Self-Learning Subjects in Hindi
Text processing is crucial for low-resource languages as it enables the development of tools and technologies that bridge the digital divide and provide equitable access to information and services.A Thousand Faces: A Persuasion Benchmark with Experience-Grounded Persuadees Informed by Psychology and Pragmatics
People can express the same beliefs and desires yet need different reasons to change their minds.Calibration-Free Early Stopping for Chain-of-Thought Reasoning via E-processes
Reasoning large language models (LLMs) benefit from test-time scaling, motivating adaptive policies that spend tokens when they help and stop early otherwise.Hidden Cartographer: Hidden State Guided Data Selection for Dual Budgeted Instruction Tuning
Given the high cost of expert annotation and limited fine-tuning resources, effective data selection from large unlabeled pools under strict budgets has become a crucial step in adapting LLMs to…Assessing the Empirical Evidence for Loss of Control from Agentic General-Purpose AI
Theoretical literature warns that advanced generalist agentic systems might pursue instrumental goals that are misaligned with human preferences, thus posing risks of irreversible loss of human…SPARC: Spoken Profile Authorship Recognition Corpus
Speech anonymization has focused on the acoustic signal, leaving open how much speaker information the transcribed words themselves retain.Aligning Language Models with Indigenous Community Cosmovision through Constitutional AI
Large language models (LLMs) are predominantly trained on corpora that reflect Western, anglophone worldviews.Learning When to Abort in Transformer Planning: A Mechanistic Study
Planning does not by itself imply the ability to recognise errors, but recognising errors can improve planning capacity.Atoms, Not Knowledge: What Production-Scale Addressed-Memory Writes Deposit
Deterministic hash-addressed conditional memory permits local post-hoc knowledge injection.Where and Why Search-Augmented LLMs Fail When Reasoning over Rapidly Evolving Knowledge
As the world changes, new information is published while older records remain online.CHSM8: A Chess Transformer that Follows Natural-Language Style Prompts
We present CHSM8, a 210M-parameter chess transformer that plays moves conditioned on a free-text description of a playing style, e.g. "go for the Sicilian Defense", "solid, safe, risk-free chess" or…Aligning Cultural Behaviors in Arabic Language Models via Preferences
Arabic LLMs have improved rapidly, but aligning them with country-specific cultural behavioral preferences remains underexplored.MemDerive: A Diagnostic Benchmark for Agent Memory over Evolving Data
Long-running agents rely on memory of their past interactions for task state, such as what has been completed and which conditions still hold.Outcome-Anchored Credit Reallocation for Agentic Knowledge Graph Question Answering
Agentic knowledge graph question answering (KGQA) requires large language models (LLMs) to solve complex questions through multi-turn interactions with a knowledge graph (KG).From Unverifiable Domain Text to Cross-Lingual RLVR via Code-Switched Task Synthesis
Reinforcement Learning with Verifiable Rewards (RLVR) can improve reasoning in large language models, but specialized non-English domains expose a data mismatch.Towards Figurative Language Understanding in Moroccan Darija: An Evaluation of Large Language Models
Figurative language remains a major challenge for Machine Translation (MT) systems, as the intended meaning of such expressions often goes beyond literal translation.Mixture-of-Memories: Low-Overhead Language Modeling with Modular Knowledge Injection
Large language models store substantial factual knowledge in their parameters, yet this knowledge is difficult to control, update, and reliably elicit at inference time.RARE: Reinforcement Learning with Adaptive Rubric Evolution for Open-Ended Generation
Verifiable rewards have advanced reinforcement learning in mathematics and code.Design Considerations in Low-Resource Archival OCR: A Case Study in Lakota
Building and expanding access to digital archives supports language reclamation and creates lasting resources for community revitalization.