· ai
[Paper] DocDancer: Towards Agentic Document-Grounded Information Seeking
Document Question Answering (DocQA) focuses on answering questions grounded in given documents, yet existing DocQA agents lack effective tool utilization and la...
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- · ai
[Paper] A Lightweight and Explainable Vision-Language Framework for Crop Disease Visual Question Answering
Visual question answering for crop disease analysis requires accurate visual understanding and reliable language generation. This work presents a lightweight vi...
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[Paper] Advancing Language Models for Code-related Tasks
Recent advances in language models (LMs) have driven significant progress in various software engineering tasks. However, existing LMs still struggle with compl...
- · ai
[Paper] All That Glisters Is Not Gold: A Benchmark for Reference-Free Counterfactual Financial Misinformation Detection
We introduce RFC Bench, a benchmark for evaluating large language models on financial misinformation under realistic news. RFC Bench operates at the paragraph l...
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[Paper] FLEx: Language Modeling with Few-shot Language Explanations
Language models have become effective at a wide range of tasks, from math problem solving to open-domain question answering. However, they still make mistakes, ...
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[Paper] LLMberjack: Guided Trimming of Debate Trees for Multi-Party Conversation Creation
We present LLMberjack, a platform for creating multi-party conversations starting from existing debates, originally structured as reply trees. The system offers...
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[Paper] ContextFocus: Activation Steering for Contextual Faithfulness in Large Language Models
Large Language Models (LLMs) encode vast amounts of parametric knowledge during pre-training. As world knowledge evolves, effective deployment increasingly depe...
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[Paper] InfiniteWeb: Scalable Web Environment Synthesis for GUI Agent Training
GUI agents that interact with graphical interfaces on behalf of users represent a promising direction for practical AI assistants. However, training such agents...
- · ai
[Paper] Layer-wise Positional Bias in Short-Context Language Modeling
Language models often show a preference for using information from specific positions in the input regardless of semantic relevance. While positional bias has b...
- · ai
[Paper] SearchAttack: Red-Teaming LLMs against Real-World Threats via Framing Unsafe Web Information-Seeking Tasks
Recently, people have suffered and become increasingly aware of the unreliability gap in LLMs for open and knowledge-intensive tasks, and thus turn to search-au...
- · ai
[Paper] KDCM: Reducing Hallucination in LLMs through Explicit Reasoning Structures
To mitigate hallucinations in large language models (LLMs), we propose a framework that focuses on errors induced by prompts. Our method extends a chain-style k...
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[Paper] Analyzing Reasoning Consistency in Large Multimodal Models under Cross-Modal Conflicts
Large Multimodal Models (LMMs) have demonstrated impressive capabilities in video reasoning via Chain-of-Thought (CoT). However, the robustness of their reasoni...