7 papers · 1 filter
Entity Binding Failures in Tool-Augmented Agents
Rahul Suresh Babu, Shashank Indukuri
Tool-augmented language-model agents are often evaluated by whether they select the correct tool, produce valid API arguments, and complete the requested task. However, an agent ma…
GIST-CMTF: Goal-State Inference for Causal Minimal Tool Filtering in LLM Agents
Rahul Suresh Babu, Rohit Shukla
Tool-augmented LLM agents rely on runtime filtering to decide which tools should be visible at each step. Causal Minimal Tool Filtering (CMTF) reduces tool-choice confusion by expo…
ToolMenuBench: Benchmarking Tool-Menu Filtering Strategies for Reliable and Efficient LLM Agents
Rahul Suresh Babu, Laxmipriya Ganesh Iyer
Tool-augmented large language model agents increasingly operate over large tool libraries, but existing evaluations often focus on whether a model can call a tool correctly rather…
Capability Minimization as a Safety Primitive: Risk-Aware Causal Gating for Least-Privilege LLM Agents
Laxmipriya Ganesh Iyer, Rahul Suresh Babu
Modern decision systems increasingly rely on learned components whose outputs may be confident yet wrong, exposing downstream actions to costly errors. We introduce Risk-Aware Caus…
Contract2Tool: Learning Preconditions and Effects for Reliable Tool-Augmented LLM Agents
Rahul Suresh Babu, Laxmipriya Ganesh Iyer
Tool-augmented large language model agents increasingly rely on external APIs, but standard tool schemas describe how to call a tool, not when the tool is causally appropriate or w…
ToolChoiceConfusion: Causal Minimal Tool Filtering for Reliable LLM Agents
Rahul Suresh Babu, Laxmipriya Ganesh Iyer
Large language model agents increasingly rely on external tools, but larger tool menus can reduce reliability and efficiency by increasing wrong-tool calls, premature actions, and…