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Computation & Language / NLP
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Newest papers, page 19
Halal-NeSyNet: Clause-Scoped Neuro-Symbolic Cross-Attention for Automated Food Ingredient Auditing and Risk-Aware Halal Logistics Triage
Verifying that a packaged food is Halal requires reading ingredient declarations and E-number additives before goods enter certified warehouses.LLM-Enhanced Multimodal House Price Prediction using Structured, Textual, and Visual Features
Accurate house price prediction is essential for real estate buyers, sellers, agents, and financial institutions.FinForesight: A Diagnostic Backtesting Benchmark for Deep Research Systems in Financial Forecasting
Anticipating financial outcomes requires synthesizing evolving evidence and reasoning under uncertainty, making deep research systems promising tools for forecasting.BanglishDepYT: Depression Detection in Native Bengali Social Media with Emotion-Preserving Preprocessing and Domain-Adaptive Pretraining
Depression affects millions of Bengali speakers across South Asia, yet automated detection systems have relied almost entirely on datasets translated from English.CREDO: Evidence-Conditioned Credit Assignment for Temporal Reasoning Agents
Temporal Knowledge Graph Question Answering (TKGQA) requires language model agents to retrieve evidence, select relevant facts, and perform multi-step temporal reasoning.EEG-HealthLLM: Hierarchical Adaptation of Large Language Models for Unified Heterogeneous EEG Health Assessment
Electroencephalography (EEG) provides a non-invasive means for neurological and mental health assessment, yet existing EEG models are typically developed for individual tasks and are difficult to…CST: Lightweight Risk Triage with Source-Grounded Evidence for Web Discussions
Web communities rely on moderators to catch harmful messages such as insults, hate speech, and scams, but no one can read every message.EarlySelectKV: Anticipatory KV Selection via Cross-Layer Query Proxies
Query-conditioned sparse KV selection reduces long-context inference cost by attending to a subset of historical KV entries at each decoding step.MAC-Bench: Benchmarking Multi-Agent Collaboration via Interconnected Tasks
Large language model (LLM)-based multi-agent systems (MAS) tackle challenging tasks by dividing work among agents and coordinating their contributions toward shared objectives.Less but Sufficient: Relation Knowledge Selects Compact Knowledge-Graph Contexts, and What External Checks Can and Cannot Catch
Large language models (LLMs) read knowledge-graph facts ranked by relevance, leaving open whether they suffice or conflict.Evolving Memory, Learning to Meta-Control: Test-Time Adaptation for Experience-augmented LLM Agents
Self-evolving agents accumulate experience from task streams, but existing frameworks typically rely on fixed pipelines to retrieve and utilize this experience, neglecting when and how to deploy it.A Bounded Evaluation Protocol for Representational Systematicity
Multiple studies have shown that neural networks can be behaviorally systematic, producing correct outputs for novel combinations of familiar parts.MemRole: From Memories to Decisions for Long-Horizon Reasoning in Role-Playing Agents
LLM-based role-playing agents are fluent at imitating a character's style, yet struggle to make role-consistent decisions over long narrative horizons.Rubric-Based Assessment of Student Reports Using Small Language Models
Language models can analyze and assess student texts using predefined rubrics and deliver structured feedback, reducing instructors' workload.Shared relations, specific choices: conditional sensitivity and competing pathways in language models
How does a relational representation shared across queries drive a query-specific choice?The Scope Grammar of Natural-Language Rules: Counting and Enumerating Readings modulo Logical Equivalence
A rule written for people fixes its atomic conditions and connectives but leaves open how the connectives are bracketed, and each bracketing is a different logical reading that an autoformalizer…LegoEnv: Self-Evolving Agentic Environments via Modular Recombination
LLM agents learn by interacting with environments, yet existing environments are designed for specific tasks and fail to generalize to new ones.Self-Evolving Agentic Workflows via Semantic Decomposition of Complex Tasks
Agentic workflows organize complex tasks into reusable procedures.Quantizing Recurrent Language Models Is Easier Than You Think
Linear recurrences are becoming an increasingly common building block in large language models, replacing the growing KV cache of softmax attention with a fixed-size recurrent state that enables…Don't Guess, Ask Wisely: Benchmarking and Training Proactive Elicitation in Open-Domain LLM Conversations
When user queries are incomplete, large language models should ask targeted questions before committing to an answer, a capability we call proactive elicitation, yet evaluation on real…