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Computation & Language / NLP
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Newest papers, page 16
Every Clause Counts: Instruction-Following Reranking by Multiplying Small, Answerable Questions
People often attach instructions to their search queries, asking for pages written for beginners, documents in a certain language or official sources only.ACTOR: Action-Centered Temporal Organization for Literary Role-Playing Agents
Large language agents for literary role-playing are typically modeled around dialogue generation, leaving characters' non-dialogue behaviors and their dynamic evolution over story time…Dhārā Bench: An Evidence-Oriented Retrieval Benchmark for Indian Knowledge Systems
Dhārā Bench is a retrieval benchmark for Indian Knowledge Systems (IKS), with 325 questions in 12 categories and 60,121 text chunks from 15 source groups.Written Once, Read Differently How Language Models Own Answers Steer Their Next Ones
When a language model answers a yes/no question, that answer changes how it answers a different question about the same entity.Do Agents Still Follow the Rules? Benchmarking Rule Compliance under Agent Context Compaction
LLM agents compact long histories to fit their context windows, but the compacted context must still carry the operating rules that govern later actions.Specificity Bias and the Wikipedia Paradox: An xAI Analysis of AI Text Detectors under Domain Shift
The widespread adoption of Large Language Models (LLMs) demands reliable detection of human-authored versus synthetic text.LLMs Depend on Specialist Tools for Out-of-Distribution Generalization in MS/MS Structural Elucidation
A frontier language model was recently reported to solve 1D NMR structural elucidation without tools.MultiInpaintCOCO: Fine-Grained Visual Understanding in Multiple Languages
Previous research shows that vision-language (VL) models struggle to understand fine-grained image details and tend to focus on the overall layout.Steering with Multilingual Lexicons for Sentiment Control in Low-Resource Languages
Activation steering offers a lightweight mechanism for controlling model behavior, but existing methods depend on sentence-level contrastive data that is unavailable for most of the world's languages.Characterizing When Language Models Take Harmful Actions to Protect Their Assigned Goals
Recent language model (LM) safety failures have largely been studied as disparate phenomena.Same Outputs, Different Scores: Auditing the Unchecked Graders of Multimodal LLM Benchmarks
Every multimodal-LLM multiple-choice benchmark ends with a scoring rule that converts a model's response, often free-form text rather than a clean option letter, into a right/wrong verdict, buried…IdeaTaste: Do LLMs Share the Research Taste of Human Researchers?
Research taste, the judgment of what to read, which problems to pursue, and which methods to try, increasingly shapes the work of AI scientists, yet it remains far less understood than their ability…Optimize the Harness, Not the Model: Fitting a Minimal Agent to a Self-Hostable LLM for Investigative Analysis
Government intelligence teams need LLM agents that can analyze large, messy evidence collections, but security and cost constraints often rule out hosted frontier models and broad, hard-to-audit…Online Label-Free Gradient Matching for Continual Language Model Training
Language models in customer-facing products must be continually updated, since the data they serve shifts over time.VIAS: Value-Isolating Activation Steering for Multi-Value Alignment and Compliance for Organisations
Organisations increasingly deploy large language model agents that must follow organisational values.Library of Layers (LoL): Adaptively Ordering Transformer Layers at Runtime
Computer programmers chain together the same reusable computational primitives, for example, conditional statements or loops, but in different orders to implement different algorithms.Can LLM Agents Be Forward-Deployed Engineers? Requirement Discovery and Delivery for Enterprise Text-to-SQL
LLM coding agents can increasingly automate model post-training, but whether they can act as forward-deployed engineer (FDE) agents, discovering customer requirements and turning them into…VeriHarm-Bench: Measuring Harmful Success in LLM Coding Agents Verifiably
Large language model (LLM) coding agents increasingly operate with shell access, allowing them to write scripts, move files, alter permissions, and modify system configurations.NitiBench+: A Temporal Thai Legal Question Answering Benchmark Across 17 Domains
Law changes over time.Sonar-MoE: In-Backward Expert Updates for Memory-Efficient Mixture-of-Experts Training
Most parameters of a Mixture-of-Experts (MoE) model belong to its experts, and standard training keeps every expert gradient in GPU memory until the optimizer step.