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Computation & Language / NLP
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Newest papers, page 143
Memento 3: Model-Based Recursive Self-Improvement through Reflective Rulebooks
Learning to act in unfamiliar environments requires agents to infer how the world works and revise that understanding as new evidence arrives.Detecting Spin in Clinical Trials with Large Language Models
Spin in clinical trials includes reporting practices that distort the presentation of results.GRPODropout: Less is More for Online Reinforcement Learning Rollouts
Reinforcement learning (RL) methods such as GRPO substantially improve large language model reasoning but often suffer from policy entropy collapse: the loss of sampling diversity weakens…Forms of LLM-Integrated Applications from LLM-Chats to Autonomous AI Agent System
Large language models (LLMs) are increasingly embedded as components in software systems, marketed under labels such as chatbot, copilot, retrieval-augmented generation, workflow, coding agent and…Can Decision Models Understand Stance? Evaluating Jev Against General-Purpose LLMs
Stance detection requires identifying an author's attitude toward a given target, sometimes based on conversational context.Not Every Change Is Necessary: Recoverable Drift in Large Language Model Unlearning
Machine unlearning in large language models aims to remove unwanted knowledge while preserving the model's remaining capabilities.Event-Centric Memory with Query-Aware Graph Augmentation for Long-Term Conversational Agents
For persistent and personalized conversational agents, memory systems can enable them to remember, update, and reason over long histories by storing past interactions and retrieving relevant…Project Greenhouse: Progress Toward Fully Open and Sovereign Agentic Search
Project Greenhouse represents our exploration of a simple thesis: We believe that it is possible to build fully open and sovereign models for agentic search with only modest computational resources.When History Helps and Hurts: Selective History Use across Multimodal Turns
Reliable multimodal interaction depends on selective use of conversational history: an earlier question may remain relevant while its previous answer is outdated, whereas a current request may…MiMo-V2.6: Scaling Reinforcement Learning Towards Self-Improvement
Reinforcement learning (RL) is the central training paradigm for advancing large foundation models towards self-improvement.MindFlow: Mind Supernet Powered Thinking Flows for Research Idea Innovation
Research idea innovation is a fundamental engine of scientific progress, yet it remains difficult to generate and evaluate in a scalable and controllable way.Specialized Decision Models vs. General-Purpose LLMs: Benchmarking Jev Across Knowledge, Reasoning, and Multilingual Tasks
Jev is a "System One" model that returns a choice among given options instead of generating text.DataVista: Diagnosing Multimodal LLMs on Data Video Understanding
Data video is a media form that integrates data visualization with video narrative, widely adopted in news reporting and business analysis.Agentic-TTT: Training test-time policy for test-time training
Test-time training (TTT) adapts an LLM's parameters using signals derived from test inputs, and can make striking improvements in pre-specified settings such as IMO competitions or designated open…Examining Social Attribution in LLM Reasoning: A Theory-Guided Probing Methodology
Large language models (LLMs) are increasingly deployed in sociotechnical systems where social attribution, the reasoning process attributing external events to the causes and reasons of agents'…InterviewPlayground: A Validated Simulation Environment for Evaluating AI Interviewers
Increasingly, AI interviewers are being developed to elicit open-ended responses in applications like market research, public polling, preference elicitation, and social science research.Natural Language to First-Order Logic LLM-based Autoformalization
Large Language Models (LLMs) have renewed interest in autoformalization.When Should Agents Think? Adaptive Reasoning via Cross-Turn Estimation
Large language model (LLM)-based agents have demonstrated strong capabilities on complex tasks.ILM: An AI-Powered Storytelling Educational Tool
Digital technologies have made Islamic narratives more accessible, but existing platforms provide limited support for structured learning and comprehension of these stories, particularly in Arabic…All Verdicts are Not Equal: Rethinking LLM Judge Reliability
LLM-as-a-Judge is the standard paradigm for NLP evaluation, yet its systemic reliability remains poorly understood despite being widely treated as a deterministic ground truth.