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Computation & Language / NLP
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Newest papers, page 190
Right-Wing Rock or Just Rock? A Computational Linguistic Analysis of Frei.Wild
Rechtsrock is a subgenre of rock music that spreads right-wing ideology, often instrumentalized to recruit adolescents into the radical scene.When the Right Answer Is Missing: An Arithmetic-Dependent Rejection Bottleneck in Jev
Typed decision models such as Jev offer an efficient alternative to generative LLMs in decision-making workflows by selecting directly from predefined options.Spike-driven Vision-Language-Action Model
Vision-language-action (VLA) models bridge multimodal understanding and robotic control, advancing the dominant paradigm for embodied intelligence.CATCH: A Controllable Analysis Testbed for Reward Hacking in Coding RL
During reinforcement learning with verifiable rewards (RLVR), large language models (LLMs) can exploit loopholes in their environments to obtain high rewards without improving the intended…Speculative Safety Honeypot: Toward Proactive Defense Against Multi-turn Agent Attacks
As Large Language Model (LLM) agents are increasingly deployed in complex environments, multi-turn interaction attacks have become a significant security challenge.Compact Language, Complex Model Shifts: How and Where Ambiguity and Underspecification Affect LLMs
We analyze how lexical ambiguity and underspecification affect language model training.Thinking Outside the Box: Can Language Models Rely on External Guidance Selectively?
Agent harnesses often improve language models with human-designed workflows, but as models grow more capable, unreliable guidance can increasingly constrain their execution.Is This Evidence Decision-Critical? Learning to Verify Rule-Governed Decisions
Rule-based reasoning, as in eligibility checks and contract reviews, requires language models to assess evidence against individual conditions and combine their judgments under explicit rules.Marginal Response Surface Elicitation for Zero-Label Tabular Learning
Tabular learning uses structured data to predict target outcomes.Zero-Compute Cross-Lingual Transferability Estimation Using Typological Feature Proxies
Cross-lingual transfer describes how knowledge in a source language benefits a target language.SEPAL: Separated Expert Pairs with Answer-Level Fusion for Reliable LLM Collaboration
Multi-agent collaboration lets large language models (LLMs) improve question answering through deliberation and feedback.The Evolution of Attention in Large Language Models: Mechanisms, Trade-offs, and Emerging Trends
Self-attention gives LLMs fine-grained, query-dependent access to context, but dense token interactions incur quadratic prefill cost and a key--value cache growing with context length.Better Supervision Is Nearby: Neighborhood On-Policy Self-Distillation
On-policy self-distillation (OPSD) trains mathematical reasoning models using a privileged teacher that sees a reference solution and supervises student-sampled prefixes.ShieldCLIP: Selective Safety Alignment for Harmful Content Mitigation in Multimodal Foundation Models
Multimodal encoders such as CLIP underlie many downstream systems, but their web-scale training data embed harmful associations that safety alignment must suppress without unnecessarily changing…A helps B while B hurts A: directed transfer in instruction-tuning mixture
Adapting a language model to a specialized corpus means choosing which instruction-tuning tasks to train on under a fixed budget, and testing one choice costs a fine-tuning run.Drift Inspector: Exploring and Measuring Scientific Drift with Atomic Contribution Claims
Scientific abstracts mix contributions with background, motivation, and meta-language, so tools that read them as-is cannot separate what a field produces from what it discusses.OverForge: Reasoning Through Strategies and Tactics Helps Cooperative Lifelong Adaptation
Cooperative language-model agents must coordinate over long horizons and adapt to changing environments and to partners with unfamiliar conventions, yet existing agents map observations to actions…LatentHarness: Learning Latent Actions for Memory and Reasoning via Counterfactual Policy Distillation
Long-context reasoning faces two complementary bottlenecks: retaining evidence across long inputs and sustaining computation across many reasoning steps.MemCodex: Self-Programming Hierarchical Memory for Language Agents
Agent memory faces heterogeneous access needs: a single-hop question may require one piece of evidence, whereas a multi-hop question must combine evidence from multiple sources.Explore-on-Graph: Hybrid Embedding-LLM Reasoning for Knowledge Graph Question Answering under Incompleteness
Large language models (LLMs) are increasingly combined with knowledge graphs (KGs) to ground reasoning in structured evidence.